Warning

This document is for an old release of Galaxy. You can alternatively view this page in the latest release if it exists or view the top of the latest release's documentation.

galaxy.datatypes package¶

Subpackages¶

Submodules¶

galaxy.datatypes.annotation module¶

class galaxy.datatypes.annotation.SnapHmm(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

file_ext = 'snaphmm'¶

edam_data = 'data_1364'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek. This method is used by various subclasses of Text.

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

sniff_prefix(file_prefix)[source]¶: SNAP model files start with zoeHMM

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.annotation.Augustus(**kwd)[source]¶

Bases: galaxy.datatypes.binary.CompressedArchive

Class describing an Augustus prediction model

file_ext = 'augustus'¶

edam_data = 'data_0950'¶

compressed = True¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

sniff(filename)[source]¶: Augustus archives always contain the same files

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.anvio module¶

Datatypes for Anvi’o https://github.com/merenlab/anvio

class galaxy.datatypes.anvio.AnvioComposite(**kwd)[source]¶

Bases: galaxy.datatypes.text.Html

Base class to use for Anvi’o composite datatypes. Generally consist of a sqlite database, plus optional additional files

file_ext = 'anvio_composite'¶

composite_type: Optional[str] = 'auto_primary_file'¶

generate_primary_file(dataset=None)[source]¶: This is called only at upload to write the html file cannot rename the datasets here - they come with the default unfortunately

get_mime()[source]¶: Returns the mime type of the datatype

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML content, used for displaying peek.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.anvio.AnvioDB(*args, **kwd)[source]¶

Bases: galaxy.datatypes.anvio.AnvioComposite

Class for AnvioDB database files.

file_ext = 'anvio_db'¶

__init__(*args, **kwd)[source]¶: Initialize the datatype

set_meta(dataset, **kwd)[source]¶: Set the anvio_basename based upon actual extra_files_path contents.

metadata_spec = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.anvio.AnvioStructureDB(*args, **kwd)[source]¶

Bases: galaxy.datatypes.anvio.AnvioDB

Class for Anvio Structure DB database files.

file_ext = 'anvio_structure_db'¶

metadata_spec = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.anvio.AnvioGenomesDB(*args, **kwd)[source]¶

Bases: galaxy.datatypes.anvio.AnvioDB

Class for Anvio Genomes DB database files.

file_ext = 'anvio_genomes_db'¶

metadata_spec = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.anvio.AnvioContigsDB(*args, **kwd)[source]¶

Bases: galaxy.datatypes.anvio.AnvioDB

Class for Anvio Contigs DB database files.

file_ext = 'anvio_contigs_db'¶

__init__(*args, **kwd)[source]¶: Initialize the datatype

metadata_spec = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.anvio.AnvioProfileDB(*args, **kwd)[source]¶

Bases: galaxy.datatypes.anvio.AnvioDB

Class for Anvio Profile DB database files.

file_ext = 'anvio_profile_db'¶

__init__(*args, **kwd)[source]¶: Initialize the datatype

metadata_spec = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.anvio.AnvioPanDB(*args, **kwd)[source]¶

Bases: galaxy.datatypes.anvio.AnvioDB

Class for Anvio Pan DB database files.

file_ext = 'anvio_pan_db'¶

metadata_spec = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.anvio.AnvioSamplesDB(*args, **kwd)[source]¶

Bases: galaxy.datatypes.anvio.AnvioDB

Class for Anvio Samples DB database files.

file_ext = 'anvio_samples_db'¶

metadata_spec = {'anvio_basename': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.assembly module¶

velvet datatypes James E Johnson - University of Minnesota for velvet assembler tool in galaxy

class galaxy.datatypes.assembly.Amos(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

Class describing the AMOS assembly file

edam_data = 'data_0925'¶

edam_format = 'format_3582'¶

file_ext = 'afg'¶

sniff_prefix(file_prefix)[source]¶

Determines whether the file is an amos assembly file format Example:

{CTG
iid:1
eid:1
seq:
CCTCTCCTGTAGAGTTCAACCGA-GCCGGTAGAGTTTTATCA
.
qlt:
DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD
.
{TLE
src:1027
off:0
clr:618,0
gap:
250 612
.
}
}

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.assembly.Sequences(**kwd)[source]¶

Bases: galaxy.datatypes.sequence.Fasta

Class describing the Sequences file generated by velveth

edam_data = 'data_0925'¶

file_ext = 'sequences'¶

sniff_prefix(file_prefix)[source]¶

Determines whether the file is a velveth produced fasta format The id line has 3 fields separated by tabs: sequence_name sequence_index category:

>SEQUENCE_0_length_35   1       1
GGATATAGGGCCAACCCAACTCAACGGCCTGTCTT
>SEQUENCE_1_length_35   2       1
CGACGAATGACAGGTCACGAATTTGGCGGGGATTA

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'sequences': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.assembly.Roadmaps(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

Class describing the Sequences file generated by velveth

edam_format = 'format_2561'¶

file_ext = 'roadmaps'¶

sniff_prefix(file_prefix)[source]¶

Determines whether the file is a velveth produced RoadMap::: 142858 21 1 ROADMAP 1 ROADMAP 2 …

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.assembly.Velvet(**kwd)[source]¶

Bases: galaxy.datatypes.text.Html

composite_type: Optional[str] = 'auto_primary_file'¶

file_ext = 'velvet'¶

__init__(**kwd)[source]¶: Initialize the datatype

generate_primary_file(dataset=None)[source]¶

regenerate_primary_file(dataset)[source]¶: cannot do this until we are setting metadata

set_meta(dataset, **kwd)[source]¶: Set the number of lines of data in dataset.

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'long_reads': <galaxy.model.metadata.MetadataElementSpec object>, 'paired_end_reads': <galaxy.model.metadata.MetadataElementSpec object>, 'short2_reads': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.binary module¶

Binary classes

class galaxy.datatypes.binary.Binary(**kwd)[source]¶

Bases: galaxy.datatypes.data.Data

Binary data

edam_format = 'format_2333'¶

static register_sniffable_binary_format(data_type, ext, type_class)[source]¶: Deprecated method.

static register_unsniffable_binary_ext(ext)[source]¶: Deprecated method.

set_peek(dataset, **kwd)[source]¶: Set the peek and blurb text

get_mime()[source]¶: Returns the mime type of the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Ab1(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing an ab1 binary sequence file

file_ext = 'ab1'¶

edam_format = 'format_3000'¶

edam_data = 'data_0924'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Idat(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Binary data in idat format

file_ext = 'idat'¶

edam_format = 'format_2058'¶

edam_data = 'data_2603'¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Cel(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Cel File format described at: http://media.affymetrix.com/support/developer/powertools/changelog/gcos-agcc/cel.html

file_ext = 'cel'¶

edam_format = 'format_1638'¶

edam_data = 'data_3110'¶

sniff(filename)[source]¶: Try to guess if the file is a Cel file. >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘affy_v_agcc.cel’) >>> Cel().sniff(fname) True >>> fname = get_test_fname(‘affy_v_3.cel’) >>> Cel().sniff(fname) True >>> fname = get_test_fname(‘affy_v_4.cel’) >>> Cel().sniff(fname) True >>> fname = get_test_fname(‘test.gal’) >>> Cel().sniff(fname) False

set_meta(dataset, **kwd)[source]¶: Set metadata for Cel file.

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'version': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.MashSketch(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Mash Sketch file. Sketches are used by the MinHash algorithm to allow fast distance estimations with low storage and memory requirements. To make a sketch, each k-mer in a sequence is hashed, which creates a pseudo-random identifier. By sorting these identifiers (hashes), a small subset from the top of the sorted list can represent the entire sequence (these are min-hashes). The more similar another sequence is, the more min-hashes it is likely to share.

file_ext = 'msh'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.CompressedArchive(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing an compressed binary file This class can be sublass’ed to implement archive filetypes that will not be unpacked by upload.py.

file_ext = 'compressed_archive'¶

compressed = True¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Meryldb(**kwd)[source]¶

Bases: galaxy.datatypes.binary.CompressedArchive

MerylDB is a tar.gz archive, with 128 files. 64 data files and 64 index files.

file_ext = 'meryldb'¶

sniff(filename)[source]¶: Try to guess if the file is a Cel file. >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘affy_v_agcc.cel’) >>> Meryldb().sniff(fname) False >>> fname = get_test_fname(‘read-db.meryldb’) >>> Meryldb().sniff(fname) True

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.DynamicCompressedArchive(**kwd)[source]¶

Bases: galaxy.datatypes.binary.CompressedArchive

matches_any(target_datatypes)[source]¶: Treat two aspects of compressed datatypes separately.

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.GzDynamicCompressedArchive(**kwd)[source]¶

Bases: galaxy.datatypes.binary.DynamicCompressedArchive

compressed_format = 'gzip'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Bz2DynamicCompressedArchive(**kwd)[source]¶

Bases: galaxy.datatypes.binary.DynamicCompressedArchive

compressed_format = 'bz2'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.CompressedZipArchive(**kwd)[source]¶

Bases: galaxy.datatypes.binary.CompressedArchive

Class describing an compressed binary file This class can be sublass’ed to implement archive filetypes that will not be unpacked by upload.py.

file_ext = 'zip'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.GenericAsn1Binary(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class for generic ASN.1 binary format

file_ext = 'asn1-binary'¶

edam_format = 'format_1966'¶

edam_data = 'data_0849'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.BamNative(**kwd)[source]¶

Bases: galaxy.datatypes.binary.CompressedArchive

Class describing a BAM binary file that is not necessarily sorted

edam_format = 'format_2572'¶

edam_data = 'data_0863'¶

file_ext = 'unsorted.bam'¶

sort_flag: Optional[str] = None¶

static merge(split_files, output_file)[source]¶

Merges BAM files

Parameters

split_files – List of bam file paths to merge
output_file – Write merged bam file to this location

init_meta(dataset, copy_from=None)[source]¶

sniff(filename)[source]¶

classmethod is_bam(filename)[source]¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

to_archive(dataset, name='')[source]¶

Collect archive paths and file handles that need to be exported when archiving dataset.

Parameters

dataset – HistoryDatasetAssociation
name – archive name, in collection context corresponds to collection name(s) and element_identifier, joined by ‘/’, e.g ‘fastq_collection/sample1/forward’

groom_dataset_content(file_name)[source]¶: Ensures that the BAM file contents are coordinate-sorted. This function is called on an output dataset after the content is initially generated.

get_chunk(trans, dataset, offset=0, ck_size=None)[source]¶

display_data(trans, dataset, preview=False, filename=None, to_ext=None, offset=None, ck_size=None, **kwd)[source]¶

Displays data in central pane if preview is True, else handles download.

Datatypes should be very careful if overridding this method and this interface between datatypes and Galaxy will likely change.

TOOD: Document alternatives to overridding this method (data providers?).

validate(dataset, **kwd)[source]¶

metadata_spec = {'bam_header': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_version': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'read_groups': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_lengths': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_names': <galaxy.model.metadata.MetadataElementSpec object>, 'sort_order': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Bam(**kwd)[source]¶

Bases: galaxy.datatypes.binary.BamNative

Class describing a BAM binary file

edam_format = 'format_2572'¶

edam_data = 'data_0863'¶

file_ext = 'bam'¶

track_type: Optional[str] = 'ReadTrack'¶

data_sources: Dict[str, str] = {'data': 'bai', 'index': 'bigwig'}¶

get_index_flag(file_name)[source]¶: Return pysam flag for bai index (default) or csi index (contig size > (2**29 - 1) )

dataset_content_needs_grooming(file_name)[source]¶: Check if file_name is a coordinate-sorted BAM file

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(file_name)[source]¶

line_dataprovider(dataset, **settings)[source]¶

regex_line_dataprovider(dataset, **settings)[source]¶

column_dataprovider(dataset, **settings)[source]¶

dict_dataprovider(dataset, **settings)[source]¶

header_dataprovider(dataset, **settings)[source]¶

id_seq_qual_dataprovider(dataset, **settings)[source]¶

genomic_region_dataprovider(dataset, **settings)[source]¶

genomic_region_dict_dataprovider(dataset, **settings)[source]¶

samtools_dataprovider(dataset, **settings)[source]¶: Generic samtools interface - all options available through settings.

dataproviders = {'base': <function Data.base_dataprovider>, 'chunk': <function Data.chunk_dataprovider>, 'chunk64': <function Data.chunk64_dataprovider>, 'column': <function Bam.column_dataprovider>, 'dict': <function Bam.dict_dataprovider>, 'genomic-region': <function Bam.genomic_region_dataprovider>, 'genomic-region-dict': <function Bam.genomic_region_dict_dataprovider>, 'header': <function Bam.header_dataprovider>, 'id-seq-qual': <function Bam.id_seq_qual_dataprovider>, 'line': <function Bam.line_dataprovider>, 'regex-line': <function Bam.regex_line_dataprovider>, 'samtools': <function Bam.samtools_dataprovider>}¶

metadata_spec = {'bam_csi_index': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_header': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_index': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_version': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'read_groups': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_lengths': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_names': <galaxy.model.metadata.MetadataElementSpec object>, 'sort_order': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.ProBam(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Bam

Class describing a BAM binary file - extended for proteomics data

edam_format = 'format_3826'¶

edam_data = 'data_0863'¶

file_ext = 'probam'¶

metadata_spec = {'bam_csi_index': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_header': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_index': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_version': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'read_groups': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_lengths': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_names': <galaxy.model.metadata.MetadataElementSpec object>, 'sort_order': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.BamInputSorted(**kwd)[source]¶

Bases: galaxy.datatypes.binary.BamNative

sort_flag: Optional[str] = '-n'¶

file_ext = 'qname_input_sorted.bam'¶: A class for BAM files that can formally be unsorted or queryname sorted. Alignments are either ordered based on the order with which the queries appear when producing the alignment, or ordered by their queryname. This notaby keeps alignments produced by paired end sequencing adjacent.

sniff(file_name)[source]¶

dataset_content_needs_grooming(file_name)[source]¶: Groom if the file is coordinate sorted

metadata_spec = {'bam_header': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_version': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'read_groups': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_lengths': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_names': <galaxy.model.metadata.MetadataElementSpec object>, 'sort_order': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.BamQuerynameSorted(**kwd)[source]¶

Bases: galaxy.datatypes.binary.BamInputSorted

A class for queryname sorted BAM files.

sort_flag: Optional[str] = '-n'¶

file_ext = 'qname_sorted.bam'¶

sniff(file_name)[source]¶

dataset_content_needs_grooming(file_name)[source]¶: Check if file_name is a queryname-sorted BAM file

metadata_spec = {'bam_header': <galaxy.model.metadata.MetadataElementSpec object>, 'bam_version': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'read_groups': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_lengths': <galaxy.model.metadata.MetadataElementSpec object>, 'reference_names': <galaxy.model.metadata.MetadataElementSpec object>, 'sort_order': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.CRAM(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

file_ext = 'cram'¶

edam_format = 'format_3462'¶

edam_data = 'format_0863'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

get_cram_version(filename)[source]¶

set_index_file(dataset, index_file)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

sniff(filename)[source]¶

metadata_spec = {'cram_index': <galaxy.model.metadata.MetadataElementSpec object>, 'cram_version': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.BaseBcf(**kwd)[source]¶

Bases: galaxy.datatypes.binary.CompressedArchive

edam_format = 'format_3020'¶

edam_data = 'data_3498'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Bcf(**kwd)[source]¶

Bases: galaxy.datatypes.binary.BaseBcf

Class describing a (BGZF-compressed) BCF file

file_ext = 'bcf'¶

sniff(filename)[source]¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Creates the index for the BCF file.

metadata_spec = {'bcf_index': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.BcfUncompressed(**kwd)[source]¶

Bases: galaxy.datatypes.binary.BaseBcf

Class describing an uncompressed BCF file

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('1.bcf_uncompressed')
>>> BcfUncompressed().sniff(fname)
True
>>> fname = get_test_fname('1.bcf')
>>> BcfUncompressed().sniff(fname)
False

file_ext = 'bcf_uncompressed'¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.H5(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing an HDF5 file

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test.mz5')
>>> H5().sniff(fname)
True
>>> fname = get_test_fname('interval.interval')
>>> H5().sniff(fname)
False

file_ext = 'h5'¶

edam_format = 'format_3590'¶

__init__(**kwd)[source]¶: Initialize the datatype

sniff(filename)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Loom(**kwd)[source]¶

Bases: galaxy.datatypes.binary.H5

Class describing a Loom file: http://loompy.org/

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test.loom')
>>> Loom().sniff(fname)
True
>>> fname = get_test_fname('test.mz5')
>>> Loom().sniff(fname)
False

file_ext = 'loom'¶

edam_format = 'format_3590'¶

sniff(filename)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

metadata_spec = {'col_attrs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'col_attrs_names': <galaxy.model.metadata.MetadataElementSpec object>, 'col_graphs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'col_graphs_names': <galaxy.model.metadata.MetadataElementSpec object>, 'creation_date': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'description': <galaxy.model.metadata.MetadataElementSpec object>, 'doi': <galaxy.model.metadata.MetadataElementSpec object>, 'layers_count': <galaxy.model.metadata.MetadataElementSpec object>, 'layers_names': <galaxy.model.metadata.MetadataElementSpec object>, 'loom_spec_version': <galaxy.model.metadata.MetadataElementSpec object>, 'row_attrs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'row_attrs_names': <galaxy.model.metadata.MetadataElementSpec object>, 'row_graphs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'row_graphs_names': <galaxy.model.metadata.MetadataElementSpec object>, 'shape': <galaxy.model.metadata.MetadataElementSpec object>, 'title': <galaxy.model.metadata.MetadataElementSpec object>, 'url': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Anndata(**kwd)[source]¶

Bases: galaxy.datatypes.binary.H5

Class describing an HDF5 anndata files: http://anndata.rtfd.io >>> from galaxy.datatypes.sniff import get_test_fname >>> Anndata().sniff(get_test_fname(‘pbmc3k_tiny.h5ad’)) True >>> Anndata().sniff(get_test_fname(‘test.mz5’)) False >>> Anndata().sniff(get_test_fname(‘import.loom.krumsiek11.h5ad’)) True >>> Anndata().sniff(get_test_fname(‘adata_0_6_small2.h5ad’)) True >>> Anndata().sniff(get_test_fname(‘adata_0_6_small.h5ad’)) True >>> Anndata().sniff(get_test_fname(‘adata_0_7_4_small2.h5ad’)) True >>> Anndata().sniff(get_test_fname(‘adata_0_7_4_small.h5ad’)) True >>> Anndata().sniff(get_test_fname(‘adata_unk2.h5ad’)) True >>> Anndata().sniff(get_test_fname(‘adata_unk.h5ad’)) True

file_ext = 'h5ad'¶

sniff(filename)[source]¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'anndata_spec_version': <galaxy.model.metadata.MetadataElementSpec object>, 'creation_date': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'description': <galaxy.model.metadata.MetadataElementSpec object>, 'doi': <galaxy.model.metadata.MetadataElementSpec object>, 'layers_count': <galaxy.model.metadata.MetadataElementSpec object>, 'layers_names': <galaxy.model.metadata.MetadataElementSpec object>, 'obs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'obs_layers': <galaxy.model.metadata.MetadataElementSpec object>, 'obs_names': <galaxy.model.metadata.MetadataElementSpec object>, 'obs_size': <galaxy.model.metadata.MetadataElementSpec object>, 'obsm_count': <galaxy.model.metadata.MetadataElementSpec object>, 'obsm_layers': <galaxy.model.metadata.MetadataElementSpec object>, 'raw_var_count': <galaxy.model.metadata.MetadataElementSpec object>, 'raw_var_layers': <galaxy.model.metadata.MetadataElementSpec object>, 'raw_var_size': <galaxy.model.metadata.MetadataElementSpec object>, 'row_attrs_count': <galaxy.model.metadata.MetadataElementSpec object>, 'shape': <galaxy.model.metadata.MetadataElementSpec object>, 'title': <galaxy.model.metadata.MetadataElementSpec object>, 'uns_count': <galaxy.model.metadata.MetadataElementSpec object>, 'uns_layers': <galaxy.model.metadata.MetadataElementSpec object>, 'url': <galaxy.model.metadata.MetadataElementSpec object>, 'var_count': <galaxy.model.metadata.MetadataElementSpec object>, 'var_layers': <galaxy.model.metadata.MetadataElementSpec object>, 'var_size': <galaxy.model.metadata.MetadataElementSpec object>, 'varm_count': <galaxy.model.metadata.MetadataElementSpec object>, 'varm_layers': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.GmxBinary(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Base class for GROMACS binary files - xtc, trr, cpt

magic_number: Optional[int] = None¶

file_ext = ''¶

sniff_prefix(sniff_prefix)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.binary.Trr(**kwd)[source]¶

Bases: galaxy.datatypes.binary.GmxBinary

Class describing an trr file from the GROMACS suite

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('md.trr')
>>> Trr().sniff(fname)
True
>>> fname = get_test_fname('interval.interval')
>>> Trr().sniff(fname)
False

file_ext = 'trr'¶

magic_number: Optional[int] = 1993¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Cpt(**kwd)[source]¶

Bases: galaxy.datatypes.binary.GmxBinary

Class describing a checkpoint (.cpt) file from the GROMACS suite

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('md.cpt')
>>> Cpt().sniff(fname)
True
>>> fname = get_test_fname('md.trr')
>>> Cpt().sniff(fname)
False

file_ext = 'cpt'¶

magic_number: Optional[int] = 171817¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Xtc(**kwd)[source]¶

Bases: galaxy.datatypes.binary.GmxBinary

Class describing an xtc file from the GROMACS suite

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('md.xtc')
>>> Xtc().sniff(fname)
True
>>> fname = get_test_fname('md.trr')
>>> Xtc().sniff(fname)
False

file_ext = 'xtc'¶

magic_number: Optional[int] = 1995¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Edr(**kwd)[source]¶

Bases: galaxy.datatypes.binary.GmxBinary

Class describing an edr file from the GROMACS suite

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('md.edr')
>>> Edr().sniff(fname)
True
>>> fname = get_test_fname('md.trr')
>>> Edr().sniff(fname)
False

file_ext = 'edr'¶

magic_number: Optional[int] = -55555¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Biom2(**kwd)[source]¶

Bases: galaxy.datatypes.binary.H5

Class describing a biom2 file (http://biom-format.org/documentation/biom_format.html)

file_ext = 'biom2'¶

edam_format = 'format_3746'¶

sniff(filename)[source]¶

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('biom2_sparse_otu_table_hdf5.biom2')
>>> Biom2().sniff(fname)
True
>>> fname = get_test_fname('test.mz5')
>>> Biom2().sniff(fname)
False
>>> fname = get_test_fname('wiggle.wig')
>>> Biom2().sniff(fname)
False

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'creation_date': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'format': <galaxy.model.metadata.MetadataElementSpec object>, 'format_url': <galaxy.model.metadata.MetadataElementSpec object>, 'format_version': <galaxy.model.metadata.MetadataElementSpec object>, 'generated_by': <galaxy.model.metadata.MetadataElementSpec object>, 'id': <galaxy.model.metadata.MetadataElementSpec object>, 'nnz': <galaxy.model.metadata.MetadataElementSpec object>, 'shape': <galaxy.model.metadata.MetadataElementSpec object>, 'type': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Cool(**kwd)[source]¶

Bases: galaxy.datatypes.binary.H5

Class describing the cool format (https://github.com/mirnylab/cooler)

file_ext = 'cool'¶

sniff(filename)[source]¶

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('matrix.cool')
>>> Cool().sniff(fname)
True
>>> fname = get_test_fname('test.mz5')
>>> Cool().sniff(fname)
False
>>> fname = get_test_fname('wiggle.wig')
>>> Cool().sniff(fname)
False
>>> fname = get_test_fname('biom2_sparse_otu_table_hdf5.biom2')
>>> Cool().sniff(fname)
False

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.MCool(**kwd)[source]¶

Bases: galaxy.datatypes.binary.H5

Class describing the multi-resolution cool format (https://github.com/mirnylab/cooler)

file_ext = 'mcool'¶

sniff(filename)[source]¶

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('matrix.mcool')
>>> MCool().sniff(fname)
True
>>> fname = get_test_fname('matrix.cool')
>>> MCool().sniff(fname)
False
>>> fname = get_test_fname('test.mz5')
>>> MCool().sniff(fname)
False
>>> fname = get_test_fname('wiggle.wig')
>>> MCool().sniff(fname)
False
>>> fname = get_test_fname('biom2_sparse_otu_table_hdf5.biom2')
>>> MCool().sniff(fname)
False

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Scf(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing an scf binary sequence file

edam_format = 'format_1632'¶

edam_data = 'data_0924'¶

file_ext = 'scf'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Sff(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Standard Flowgram Format (SFF)

edam_format = 'format_3284'¶

edam_data = 'data_0924'¶

file_ext = 'sff'¶

sniff_prefix(sniff_prefix)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.binary.BigWig(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Accessing binary BigWig files from UCSC. The supplemental info in the paper has the binary details: http://bioinformatics.oxfordjournals.org/cgi/content/abstract/btq351v1

edam_format = 'format_3006'¶

edam_data = 'data_3002'¶

file_ext = 'bigwig'¶

track_type: Optional[str] = 'LineTrack'¶

data_sources: Dict[str, str] = {'data_standalone': 'bigwig'}¶

__init__(**kwd)[source]¶: Initialize the datatype

sniff_prefix(sniff_prefix)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.binary.BigBed(**kwd)[source]¶

Bases: galaxy.datatypes.binary.BigWig

BigBed support from UCSC.

edam_format = 'format_3004'¶

edam_data = 'data_3002'¶

file_ext = 'bigbed'¶

data_sources: Dict[str, str] = {'data_standalone': 'bigbed'}¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.TwoBit(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing a TwoBit format nucleotide file

edam_format = 'format_3009'¶

edam_data = 'data_0848'¶

file_ext = 'twobit'¶

sniff_prefix(sniff_prefix)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.binary.SQlite(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing a Sqlite database

file_ext = 'sqlite'¶

edam_format = 'format_3621'¶

init_meta(dataset, copy_from=None)[source]¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

sniff_table_names(filename, table_names)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

sqlite_dataprovider(dataset, **settings)[source]¶

sqlite_datatableprovider(dataset, **settings)[source]¶

sqlite_datadictprovider(dataset, **settings)[source]¶

dataproviders = {'base': <function Data.base_dataprovider>, 'chunk': <function Data.chunk_dataprovider>, 'chunk64': <function Data.chunk64_dataprovider>, 'sqlite': <function SQlite.sqlite_dataprovider>, 'sqlite-dict': <function SQlite.sqlite_datadictprovider>, 'sqlite-table': <function SQlite.sqlite_datatableprovider>}¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.GeminiSQLite(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing a Gemini Sqlite database

file_ext = 'gemini.sqlite'¶

edam_format = 'format_3622'¶

edam_data = 'data_3498'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'gemini_version': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.ChiraSQLite(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing a ChiRAViz Sqlite database

file_ext = 'chira.sqlite'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.CuffDiffSQlite(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing a CuffDiff SQLite database

file_ext = 'cuffdiff.sqlite'¶

edam_format = 'format_3621'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'cuffdiff_version': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'genes': <galaxy.model.metadata.MetadataElementSpec object>, 'samples': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.MzSQlite(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing a Proteomics Sqlite database

file_ext = 'mz.sqlite'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.PQP(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing a Peptide query parameters file

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test.pqp')
>>> PQP().sniff(fname)
True
>>> fname = get_test_fname('test.osw')
>>> PQP().sniff(fname)
False

file_ext = 'pqp'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶: table definition according to https://github.com/grosenberger/OpenMS/blob/develop/src/openms/source/ANALYSIS/OPENSWATH/TransitionPQPFile.cpp#L264 for now VERSION GENE PEPTIDE_GENE_MAPPING are excluded, since there is test data wo these tables, see also here https://github.com/OpenMS/OpenMS/issues/4365

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.OSW(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing OpenSwath output

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test.osw')
>>> OSW().sniff(fname)
True
>>> fname = get_test_fname('test.sqmass')
>>> OSW().sniff(fname)
False

file_ext = 'osw'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.SQmass(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing a Sqmass database

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test.sqmass')
>>> SQmass().sniff(fname)
True
>>> fname = get_test_fname('test.pqp')
>>> SQmass().sniff(fname)
False

file_ext = 'sqmass'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.BlibSQlite(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing a Proteomics Spectral Library Sqlite database

file_ext = 'blib'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

metadata_spec = {'blib_version': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.DlibSQlite(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing a Proteomics Spectral Library Sqlite database DLIBs only have the “entries”, “metadata”, and “peptidetoprotein” tables populated. ELIBs have the rest of the tables populated too, such as “peptidequants” or “peptidescores”.

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test.dlib')
>>> DlibSQlite().sniff(fname)
True
>>> fname = get_test_fname('interval.interval')
>>> DlibSQlite().sniff(fname)
False

file_ext = 'dlib'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'dlib_version': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.ElibSQlite(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing a Proteomics Chromatagram Library Sqlite database DLIBs only have the “entries”, “metadata”, and “peptidetoprotein” tables populated. ELIBs have the rest of the tables populated too, such as “peptidequants” or “peptidescores”.

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test.elib')
>>> ElibSQlite().sniff(fname)
True
>>> fname = get_test_fname('test.dlib')
>>> ElibSQlite().sniff(fname)
False

file_ext = 'elib'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>, 'version': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.IdpDB(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing an IDPicker 3 idpDB (sqlite) database

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test.idpdb')
>>> IdpDB().sniff(fname)
True
>>> fname = get_test_fname('interval.interval')
>>> IdpDB().sniff(fname)
False

file_ext = 'idpdb'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.GAFASQLite(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing a GAFA SQLite database

file_ext = 'gafa.sqlite'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'gafa_schema_version': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.NcbiTaxonomySQlite(**kwd)[source]¶

Bases: galaxy.datatypes.binary.SQlite

Class describing the NCBI Taxonomy database stored in SQLite as done by rust-ncbitaxonomy

file_ext = 'ncbitaxonomy.sqlite'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'ncbitaxonomy_schema_version': <galaxy.model.metadata.MetadataElementSpec object>, 'table_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'table_row_count': <galaxy.model.metadata.MetadataElementSpec object>, 'tables': <galaxy.model.metadata.MetadataElementSpec object>, 'taxon_count': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Xlsx(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class for Excel 2007 (xlsx) files

file_ext = 'xlsx'¶

compressed = True¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.ExcelXls(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing an Excel (xls) file

file_ext = 'excel.xls'¶

edam_format = 'format_3468'¶

sniff(filename)[source]¶

get_mime()[source]¶: Returns the mime type of the datatype

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Sra(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Sequence Read Archive (SRA) datatype originally from mdshw5/sra-tools-galaxy

file_ext = 'sra'¶

sniff_prefix(sniff_prefix)[source]¶: The first 8 bytes of any NCBI sra file is ‘NCBI.sra’, and the file is binary. For details about the format, see http://www.ncbi.nlm.nih.gov/books/n/helpsra/SRA_Overview_BK/#SRA_Overview_BK.4_SRA_Data_Structure

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.binary.RData(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Generic R Data file datatype implementation

file_ext = 'rdata'¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.OxliBinary(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.OxliCountGraph(**kwd)[source]¶

Bases: galaxy.datatypes.binary.OxliBinary

OxliCountGraph starts with “OXLI” + one byte version number + 8-bit binary ‘1’ Test file generated via:

load-into-counting.py --n_tables 1 --max-tablesize 1 \
    oxli_countgraph.oxlicg khmer/tests/test-data/100-reads.fq.bz2

using khmer 2.0

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('sequence.csfasta')
>>> OxliCountGraph().sniff(fname)
False
>>> fname = get_test_fname("oxli_countgraph.oxlicg")
>>> OxliCountGraph().sniff(fname)
True

file_ext = 'oxlicg'¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.OxliNodeGraph(**kwd)[source]¶

Bases: galaxy.datatypes.binary.OxliBinary

OxliNodeGraph starts with “OXLI” + one byte version number + 8-bit binary ‘2’ Test file generated via:

load-graph.py --n_tables 1 --max-tablesize 1 oxli_nodegraph.oxling \
    khmer/tests/test-data/100-reads.fq.bz2

using khmer 2.0

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('sequence.csfasta')
>>> OxliNodeGraph().sniff(fname)
False
>>> fname = get_test_fname("oxli_nodegraph.oxling")
>>> OxliNodeGraph().sniff(fname)
True

file_ext = 'oxling'¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.OxliTagSet(**kwd)[source]¶

Bases: galaxy.datatypes.binary.OxliBinary

OxliTagSet starts with “OXLI” + one byte version number + 8-bit binary ‘3’ Test file generated via:

load-graph.py --n_tables 1 --max-tablesize 1 oxli_nodegraph.oxling \
    khmer/tests/test-data/100-reads.fq.bz2;
mv oxli_nodegraph.oxling.tagset oxli_tagset.oxlits

using khmer 2.0

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('sequence.csfasta')
>>> OxliTagSet().sniff(fname)
False
>>> fname = get_test_fname("oxli_tagset.oxlits")
>>> OxliTagSet().sniff(fname)
True

file_ext = 'oxlits'¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.OxliStopTags(**kwd)[source]¶

Bases: galaxy.datatypes.binary.OxliBinary

OxliStopTags starts with “OXLI” + one byte version number + 8-bit binary ‘4’ Test file adapted from khmer 2.0’s “khmer/tests/test-data/goodversion-k32.stoptags”

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('sequence.csfasta')
>>> OxliStopTags().sniff(fname)
False
>>> fname = get_test_fname("oxli_stoptags.oxlist")
>>> OxliStopTags().sniff(fname)
True

file_ext = 'oxlist'¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.OxliSubset(**kwd)[source]¶

Bases: galaxy.datatypes.binary.OxliBinary

OxliSubset starts with “OXLI” + one byte version number + 8-bit binary ‘5’ Test file generated via:

load-graph.py -k 20 example tests/test-data/random-20-a.fa;
partition-graph.py example;
mv example.subset.0.pmap oxli_subset.oxliss

using khmer 2.0

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('sequence.csfasta')
>>> OxliSubset().sniff(fname)
False
>>> fname = get_test_fname("oxli_subset.oxliss")
>>> OxliSubset().sniff(fname)
True

file_ext = 'oxliss'¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.OxliGraphLabels(**kwd)[source]¶

Bases: galaxy.datatypes.binary.OxliBinary

OxliGraphLabels starts with “OXLI” + one byte version number + 8-bit binary ‘6’ Test file generated via:

python -c "from khmer import GraphLabels; \
    gl = GraphLabels(20, 1e7, 4); \
    gl.consume_fasta_and_tag_with_labels('tests/test-data/test-labels.fa'); \
    gl.save_labels_and_tags('oxli_graphlabels.oxligl')"

using khmer 2.0

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('sequence.csfasta')
>>> OxliGraphLabels().sniff(fname)
False
>>> fname = get_test_fname("oxli_graphlabels.oxligl")
>>> OxliGraphLabels().sniff(fname)
True

file_ext = 'oxligl'¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.PostgresqlArchive(**kwd)[source]¶

Bases: galaxy.datatypes.binary.CompressedArchive

Class describing a Postgresql database packed into a tar archive

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('postgresql_fake.tar.bz2')
>>> PostgresqlArchive().sniff(fname)
True
>>> fname = get_test_fname('test.fast5.tar')
>>> PostgresqlArchive().sniff(fname)
False

file_ext = 'postgresql'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'version': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Fast5Archive(**kwd)[source]¶

Bases: galaxy.datatypes.binary.CompressedArchive

Class describing a FAST5 archive

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test.fast5.tar')
>>> Fast5Archive().sniff(fname)
True

file_ext = 'fast5.tar'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fast5_count': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Fast5ArchiveGz(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Fast5Archive

Class describing a gzip-compressed FAST5 archive

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test.fast5.tar.gz')
>>> Fast5ArchiveGz().sniff(fname)
True
>>> fname = get_test_fname('test.fast5.tar.bz2')
>>> Fast5ArchiveGz().sniff(fname)
False
>>> fname = get_test_fname('test.fast5.tar')
>>> Fast5ArchiveGz().sniff(fname)
False

file_ext = 'fast5.tar.gz'¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fast5_count': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Fast5ArchiveBz2(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Fast5Archive

Class describing a bzip2-compressed FAST5 archive

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test.fast5.tar.bz2')
>>> Fast5ArchiveBz2().sniff(fname)
True
>>> fname = get_test_fname('test.fast5.tar.gz')
>>> Fast5ArchiveBz2().sniff(fname)
False
>>> fname = get_test_fname('test.fast5.tar')
>>> Fast5ArchiveBz2().sniff(fname)
False

file_ext = 'fast5.tar.bz2'¶

sniff(filename)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fast5_count': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.SearchGuiArchive(**kwd)[source]¶

Bases: galaxy.datatypes.binary.CompressedArchive

Class describing a SearchGUI archive

file_ext = 'searchgui_archive'¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

sniff(filename)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'searchgui_major_version': <galaxy.model.metadata.MetadataElementSpec object>, 'searchgui_version': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.NetCDF(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Binary data in netCDF format

file_ext = 'netcdf'¶

edam_format = 'format_3650'¶

edam_data = 'data_0943'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

sniff_prefix(sniff_prefix)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.binary.Dcd(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing a dcd file from the CHARMM molecular simulation program

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test_glucose_vacuum.dcd')
>>> Dcd().sniff(fname)
True
>>> fname = get_test_fname('interval.interval')
>>> Dcd().sniff(fname)
False

file_ext = 'dcd'¶

edam_data = 'data_3842'¶

__init__(**kwd)[source]¶: Initialize the datatype

sniff(filename)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Vel(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing a velocity file from the CHARMM molecular simulation program

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('test_charmm.vel')
>>> Vel().sniff(fname)
True
>>> fname = get_test_fname('interval.interval')
>>> Vel().sniff(fname)
False

file_ext = 'vel'¶

__init__(**kwd)[source]¶: Initialize the datatype

sniff(filename)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.DAA(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing an DAA (diamond alignment archive) file >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘diamond.daa’) >>> DAA().sniff(fname) True >>> fname = get_test_fname(‘interval.interval’) >>> DAA().sniff(fname) False

file_ext = 'daa'¶

__init__(**kwd)[source]¶: Initialize the datatype

sniff_prefix(sniff_prefix)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.binary.RMA6(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing an RMA6 (MEGAN6 read-match archive) file >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘diamond.rma6’) >>> RMA6().sniff(fname) True >>> fname = get_test_fname(‘interval.interval’) >>> RMA6().sniff(fname) False

file_ext = 'rma6'¶

__init__(**kwd)[source]¶: Initialize the datatype

sniff_prefix(sniff_prefix)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.binary.DMND(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing an DMND file >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘diamond_db.dmnd’) >>> DMND().sniff(fname) True >>> fname = get_test_fname(‘interval.interval’) >>> DMND().sniff(fname) False

file_ext = 'dmnd'¶

__init__(**kwd)[source]¶: Initialize the datatype

sniff_prefix(sniff_prefix)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.binary.ICM(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing an ICM (interpolated context model) file, used by Glimmer

file_ext = 'icm'¶

edam_data = 'data_0950'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

sniff(dataset)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.Parquet(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Class describing Apache Parquet file (https://parquet.apache.org/) >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘example.parquet’) >>> Parquet().sniff(fname) True >>> fname = get_test_fname(‘test.mz5’) >>> Parquet().sniff(fname) False

file_ext = 'parquet'¶

__init__(**kwd)[source]¶: Initialize the datatype

sniff_prefix(sniff_prefix)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.binary.BafTar(**kwd)[source]¶

Bases: galaxy.datatypes.binary.CompressedArchive

Base class for common behavior of tar files of directory-based raw file formats >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘brukerbaf.d.tar’) >>> BafTar().sniff(fname) True >>> fname = get_test_fname(‘test.fast5.tar’) >>> BafTar().sniff(fname) False

edam_data = 'data_2536'¶

edam_format = 'format_3712'¶

file_ext = 'brukerbaf.d.tar'¶

get_signature_file()[source]¶

sniff(filename)[source]¶

get_type()[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.YepTar(**kwd)[source]¶

Bases: galaxy.datatypes.binary.BafTar

A tar’d up .d directory containing Agilent/Bruker YEP format data

file_ext = 'agilentbrukeryep.d.tar'¶

get_signature_file()[source]¶

get_type()[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.TdfTar(**kwd)[source]¶

Bases: galaxy.datatypes.binary.BafTar

A tar’d up .d directory containing Bruker TDF format data

file_ext = 'brukertdf.d.tar'¶

get_signature_file()[source]¶

get_type()[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.MassHunterTar(**kwd)[source]¶

Bases: galaxy.datatypes.binary.BafTar

A tar’d up .d directory containing Agilent MassHunter format data

file_ext = 'agilentmasshunter.d.tar'¶

get_signature_file()[source]¶

get_type()[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.MassLynxTar(**kwd)[source]¶

Bases: galaxy.datatypes.binary.BafTar

A tar’d up .d directory containing Waters MassLynx format data

file_ext = 'watersmasslynx.raw.tar'¶

get_signature_file()[source]¶

get_type()[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.binary.WiffTar(**kwd)[source]¶

Bases: galaxy.datatypes.binary.BafTar

A tar’d up .wiff/.scan pair containing Sciex WIFF format data >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘some.wiff.tar’) >>> WiffTar().sniff(fname) True >>> fname = get_test_fname(‘brukerbaf.d.tar’) >>> WiffTar().sniff(fname) False >>> fname = get_test_fname(‘test.fast5.tar’) >>> WiffTar().sniff(fname) False

file_ext = 'wiff.tar'¶

sniff(filename)[source]¶

get_type()[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.blast module¶

NCBI BLAST datatypes.

Covers the blastxml format and the BLAST databases.

class galaxy.datatypes.blast.BlastXml(**kwd)[source]¶

Bases: galaxy.datatypes.xml.GenericXml

NCBI Blast XML Output data

file_ext = 'blastxml'¶

edam_format = 'format_3331'¶

edam_data = 'data_0857'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

sniff_prefix(file_prefix)[source]¶

Determines whether the file is blastxml

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('megablast_xml_parser_test1.blastxml')
>>> BlastXml().sniff(fname)
True
>>> fname = get_test_fname('tblastn_four_human_vs_rhodopsin.blastxml')
>>> BlastXml().sniff(fname)
True
>>> fname = get_test_fname('interval.interval')
>>> BlastXml().sniff(fname)
False

static merge(split_files, output_file)[source]¶: Merging multiple XML files is non-trivial and must be done in subclasses.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.blast.BlastNucDb(**kwd)[source]¶

Bases: galaxy.datatypes.blast._BlastDb

Class for nucleotide BLAST database files.

file_ext = 'blastdbn'¶

composite_type: Optional[str] = 'basic'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.blast.BlastProtDb(**kwd)[source]¶

Bases: galaxy.datatypes.blast._BlastDb

Class for protein BLAST database files.

file_ext = 'blastdbp'¶

composite_type: Optional[str] = 'basic'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.blast.BlastDomainDb(**kwd)[source]¶

Bases: galaxy.datatypes.blast._BlastDb

Class for domain BLAST database files.

file_ext = 'blastdbd'¶

composite_type: Optional[str] = 'basic'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.blast.LastDb(**kwd)[source]¶

Bases: galaxy.datatypes.data.Data

Class for LAST database files.

file_ext = 'lastdb'¶

composite_type: Optional[str] = 'basic'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text.

display_peek(dataset)[source]¶: Create HTML content, used for displaying peek.

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.blast.BlastNucDb5(**kwd)[source]¶

Bases: galaxy.datatypes.blast._BlastDb

Class for nucleotide BLAST database files.

file_ext = 'blastdbn5'¶

composite_type: Optional[str] = 'basic'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.blast.BlastProtDb5(**kwd)[source]¶

Bases: galaxy.datatypes.blast._BlastDb

Class for protein BLAST database files.

file_ext = 'blastdbp5'¶

composite_type: Optional[str] = 'basic'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.blast.BlastDomainDb5(**kwd)[source]¶

Bases: galaxy.datatypes.blast._BlastDb

Class for domain BLAST database files.

file_ext = 'blastdbd5'¶

composite_type: Optional[str] = 'basic'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.checkers module¶

Module proxies galaxy.util.checkers for backward compatibility.

External datatypes may make use of these functions.

galaxy.datatypes.checkers.check_binary(name, file_path=True)[source]¶

galaxy.datatypes.checkers.check_bz2(file_path, check_content=True)[source]¶

galaxy.datatypes.checkers.check_gzip(file_path, check_content=True)[source]¶

galaxy.datatypes.checkers.check_html(name, file_path=True)[source]¶: Returns True if the file/string contains HTML code.

galaxy.datatypes.checkers.check_image(file_path)[source]¶: Simple wrapper around image_type to yield a True/False verdict

galaxy.datatypes.checkers.check_zip(file_path, check_content=True, files=1)[source]¶

galaxy.datatypes.checkers.is_gzip(file_path)[source]¶

galaxy.datatypes.checkers.is_bz2(file_path)[source]¶

galaxy.datatypes.chrominfo module¶

class galaxy.datatypes.chrominfo.ChromInfo(**kwd)[source]¶

Bases: galaxy.datatypes.tabular.Tabular

file_ext = 'len'¶

metadata_spec = {'chrom': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'length': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.constructive_solid_geometry module¶

Constructive Solid Geometry file formats.

class galaxy.datatypes.constructive_solid_geometry.Ply(**kwd)[source]¶

Bases: object

The PLY format describes an object as a collection of vertices, faces and other elements, along with properties such as color and normal direction that can be attached to these elements. A PLY file contains the description of exactly one object.

subtype = ''¶

abstract __init__(**kwd)[source]¶: Initialize self. See help(type(self)) for accurate signature.

sniff_prefix(file_prefix)[source]¶: The structure of a typical PLY file: Header, Vertex List, Face List, (lists of other elements)

set_meta(dataset, **kwd)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶

display_peek(dataset)[source]¶

sniff(filename)¶

class galaxy.datatypes.constructive_solid_geometry.PlyAscii(**kwd)[source]¶

Bases: galaxy.datatypes.constructive_solid_geometry.Ply, galaxy.datatypes.data.Text

file_ext = 'plyascii'¶

subtype = 'ascii'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'face': <galaxy.model.metadata.MetadataElementSpec object>, 'file_format': <galaxy.model.metadata.MetadataElementSpec object>, 'other_elements': <galaxy.model.metadata.MetadataElementSpec object>, 'vertex': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.constructive_solid_geometry.PlyBinary(**kwd)[source]¶

Bases: galaxy.datatypes.constructive_solid_geometry.Ply, galaxy.datatypes.binary.Binary

file_ext = 'plybinary'¶

subtype = 'binary'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'face': <galaxy.model.metadata.MetadataElementSpec object>, 'file_format': <galaxy.model.metadata.MetadataElementSpec object>, 'other_elements': <galaxy.model.metadata.MetadataElementSpec object>, 'vertex': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.constructive_solid_geometry.Vtk(**kwd)[source]¶

Bases: object

The Visualization Toolkit provides a number of source and writer objects to read and write popular data file formats. The Visualization Toolkit also provides some of its own file formats.

There are two different styles of file formats available in VTK. The simplest are the legacy, serial formats that are easy to read and write either by hand or programmatically. However, these formats are less flexible than the XML based file formats which support random access, parallel I/O, and portable data compression and are preferred to the serial VTK file formats whenever possible.

All keyword phrases are written in ASCII form whether the file is binary or ASCII. The binary section of the file (if in binary form) is the data proper; i.e., the numbers that define points coordinates, scalars, cell indices, and so forth.

Binary data must be placed into the file immediately after the newline (‘\n’) character from the previous ASCII keyword and parameter sequence.

TODO: only legacy formats are currently supported and support for XML formats should be added.

subtype = ''¶

abstract __init__(**kwd)[source]¶: Initialize self. See help(type(self)) for accurate signature.

sniff_prefix(file_prefix)[source]¶: VTK files can be either ASCII or binary, with two different styles of file formats: legacy or XML. We’ll assume if the file contains a valid VTK header, then it is a valid VTK file.

set_meta(dataset, **kwd)[source]¶

set_initial_metadata(i, line, dataset)[source]¶

set_structure_metadata(line, dataset, dataset_type)[source]¶: The fourth part of legacy VTK files is the dataset structure. The geometry part describes the geometry and topology of the dataset. This part begins with a line containing the keyword DATASET followed by a keyword describing the type of dataset. Then, depending upon the type of dataset, other keyword/ data combinations define the actual data.

get_blurb(dataset)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶

display_peek(dataset)[source]¶

sniff(filename)¶

class galaxy.datatypes.constructive_solid_geometry.VtkAscii(**kwd)[source]¶

Bases: galaxy.datatypes.constructive_solid_geometry.Vtk, galaxy.datatypes.data.Text

file_ext = 'vtkascii'¶

subtype = 'ASCII'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'cells': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dataset_type': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'dimensions': <galaxy.model.metadata.MetadataElementSpec object>, 'field_components': <galaxy.model.metadata.MetadataElementSpec object>, 'field_names': <galaxy.model.metadata.MetadataElementSpec object>, 'file_format': <galaxy.model.metadata.MetadataElementSpec object>, 'lines': <galaxy.model.metadata.MetadataElementSpec object>, 'origin': <galaxy.model.metadata.MetadataElementSpec object>, 'points': <galaxy.model.metadata.MetadataElementSpec object>, 'polygons': <galaxy.model.metadata.MetadataElementSpec object>, 'spacing': <galaxy.model.metadata.MetadataElementSpec object>, 'triangle_strips': <galaxy.model.metadata.MetadataElementSpec object>, 'vertices': <galaxy.model.metadata.MetadataElementSpec object>, 'vtk_version': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.constructive_solid_geometry.VtkBinary(**kwd)[source]¶

Bases: galaxy.datatypes.constructive_solid_geometry.Vtk, galaxy.datatypes.binary.Binary

file_ext = 'vtkbinary'¶

subtype = 'BINARY'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'cells': <galaxy.model.metadata.MetadataElementSpec object>, 'dataset_type': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'dimensions': <galaxy.model.metadata.MetadataElementSpec object>, 'field_components': <galaxy.model.metadata.MetadataElementSpec object>, 'field_names': <galaxy.model.metadata.MetadataElementSpec object>, 'file_format': <galaxy.model.metadata.MetadataElementSpec object>, 'lines': <galaxy.model.metadata.MetadataElementSpec object>, 'origin': <galaxy.model.metadata.MetadataElementSpec object>, 'points': <galaxy.model.metadata.MetadataElementSpec object>, 'polygons': <galaxy.model.metadata.MetadataElementSpec object>, 'spacing': <galaxy.model.metadata.MetadataElementSpec object>, 'triangle_strips': <galaxy.model.metadata.MetadataElementSpec object>, 'vertices': <galaxy.model.metadata.MetadataElementSpec object>, 'vtk_version': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.constructive_solid_geometry.STL(**kwd)[source]¶

Bases: galaxy.datatypes.data.Data

file_ext = 'stl'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.constructive_solid_geometry.get_next_line(fh)[source]¶

galaxy.datatypes.coverage module¶

Coverage datatypes

class galaxy.datatypes.coverage.LastzCoverage(**kwd)[source]¶

Bases: galaxy.datatypes.tabular.Tabular

file_ext = 'coverage'¶

get_track_resolution(dataset, start, end)[source]¶

metadata_spec = {'chromCol': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'forwardCol': <galaxy.model.metadata.MetadataElementSpec object>, 'positionCol': <galaxy.model.metadata.MetadataElementSpec object>, 'reverseCol': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.data module¶

class galaxy.datatypes.data.DatatypeValidation(state, message)[source]¶

Bases: object

__init__(state, message)[source]¶: Initialize self. See help(type(self)) for accurate signature.

static validated()[source]¶

static invalid(message)[source]¶

static unvalidated()[source]¶

galaxy.datatypes.data.validate(dataset_instance)[source]¶

class galaxy.datatypes.data.DataMeta(name, bases, namespace, **kwargs)[source]¶

Bases: abc.ABCMeta

Metaclass for Data class. Sets up metadata spec.

__init__(name, bases, dict_)[source]¶: Initialize self. See help(type(self)) for accurate signature.

class galaxy.datatypes.data.Data(**kwd)[source]¶

Bases: object

Base class for all datatypes. Implements basic interfaces as well as class methods for metadata.

>>> class DataTest( Data ):
...     MetadataElement( name="test" )
...
>>> DataTest.metadata_spec.test.name
'test'
>>> DataTest.metadata_spec.test.desc
'test'
>>> type( DataTest.metadata_spec.test.param )
<class 'galaxy.model.metadata.MetadataParameter'>

edam_data = 'data_0006'¶

edam_format = 'format_1915'¶

file_ext = 'data'¶

CHUNKABLE = False¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶: Dictionary of metadata fields for this datatype

copy_safe_peek = True¶

is_binary = True¶

composite_type: Optional[str] = None¶

primary_file_name = 'index'¶

allow_datatype_change: Optional[bool] = None¶

track_type: Optional[str] = None¶

data_sources: Dict[str, str] = {}¶

__init__(**kwd)[source]¶: Initialize the datatype

supported_display_apps: Dict[str, Any] = {}¶

composite_files: Dict[str, Any] = {}¶

classmethod is_datatype_change_allowed()[source]¶: Returns the value of the allow_datatype_change class attribute if set in a subclass, or True iff the datatype is not composite.

get_raw_data(dataset)[source]¶: Returns the full data. To stream it open the file_name and read/write as needed

dataset_content_needs_grooming(file_name)[source]¶: This function is called on an output dataset file after the content is initially generated.

groom_dataset_content(file_name)[source]¶: This function is called on an output dataset file if dataset_content_needs_grooming returns True.

init_meta(dataset, copy_from=None)[source]¶

set_meta(dataset: Any, overwrite=True, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

missing_meta(dataset, check=None, skip=None)[source]¶: Checks for empty metadata values, Returns True if non-optional metadata is missing Specifying a list of ‘check’ values will only check those names provided; when used, optionality is ignored Specifying a list of ‘skip’ items will return True even when a named metadata value is missing

set_max_optional_metadata_filesize(max_value)[source]¶

get_max_optional_metadata_filesize()[source]¶

property max_optional_metadata_filesize¶

set_peek(dataset, is_multi_byte=False)[source]¶

Set the peek and blurb text

Parameters: is_multi_byte (bool) – deprecated

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

to_archive(dataset, name='')[source]¶

Collect archive paths and file handles that need to be exported when archiving dataset.

Parameters

dataset – HistoryDatasetAssociation
name – archive name, in collection context corresponds to collection name(s) and element_identifier, joined by ‘/’, e.g ‘fastq_collection/sample1/forward’

display_data(trans, data, preview=False, filename=None, to_ext=None, **kwd)[source]¶

Displays data in central pane if preview is True, else handles download.

Datatypes should be very careful if overridding this method and this interface between datatypes and Galaxy will likely change.

TOOD: Document alternatives to overridding this method (data providers?).

display_as_markdown(dataset_instance, markdown_format_helpers)[source]¶

Prepare for embedding dataset into a basic Markdown document.

This is a somewhat experimental interface and should not be implemented on datatypes not tightly tied to a Galaxy version (e.g. datatypes in the Tool Shed).

Speaking very losely - the datatype should should load a bounded amount of data from the supplied dataset instance and prepare for embedding it into Markdown. This should be relatively vanilla Markdown - the result of this is bleached and it should not contain nested Galaxy Markdown directives.

If the data cannot reasonably be displayed, just indicate this and do not throw an exception.

display_name(dataset)[source]¶: Returns formatted html of dataset name

display_info(dataset)[source]¶: Returns formatted html of dataset info

repair_methods(dataset)[source]¶: Unimplemented method, returns dict with method/option for repairing errors

get_mime()[source]¶: Returns the mime type of the datatype

add_display_app(app_id, label, file_function, links_function)[source]¶: Adds a display app to the datatype. app_id is a unique id label is the primary display label, e.g., display at ‘UCSC’ file_function is a string containing the name of the function that returns a properly formatted display links_function is a string containing the name of the function that returns a list of (link_name,link)

remove_display_app(app_id)[source]¶: Removes a display app from the datatype

clear_display_apps()[source]¶

add_display_application(display_application)[source]¶: New style display applications

get_display_application(key, default=None)[source]¶

get_display_applications_by_dataset(dataset, trans)[source]¶

get_display_types()[source]¶: Returns display types available

get_display_label(type)[source]¶: Returns primary label for display app

as_display_type(dataset, type, **kwd)[source]¶: Returns modified file contents for a particular display type

get_display_links(dataset, type, app, base_url, target_frame='_blank', **kwd)[source]¶: Returns a list of tuples of (name, link) for a particular display type. No check on ‘access’ permissions is done here - if you can view the dataset, you can also save it or send it to a destination outside of Galaxy, so Galaxy security restrictions do not apply anyway.

get_converter_types(original_dataset, datatypes_registry)[source]¶: Returns available converters by type for this dataset

find_conversion_destination(dataset, accepted_formats, datatypes_registry, **kwd)[source]¶: Returns ( direct_match, converted_ext, existing converted dataset )

convert_dataset(trans, original_dataset, target_type, return_output=False, visible=True, deps=None, target_context=None, history=None)[source]¶: This function adds a job to the queue to convert a dataset to another type. Returns a message about success/failure.

after_setting_metadata(dataset)[source]¶: This function is called on the dataset after metadata is set.

before_setting_metadata(dataset)[source]¶: This function is called on the dataset before metadata is set.

add_composite_file(name, **kwds)[source]¶

property writable_files¶

get_composite_files(dataset=None)[source]¶

generate_primary_file(dataset=None)[source]¶

property has_resolution¶

matches_any(target_datatypes)[source]¶: Check if this datatype is of any of the target_datatypes or is a subtype thereof.

static merge(split_files, output_file)[source]¶: Merge files with copy.copyfileobj() will not hit the max argument limitation of cat. gz and bz2 files are also working.

get_visualizations(dataset)[source]¶: Returns a list of visualizations for datatype.

has_dataprovider(data_format)[source]¶: Returns True if data_format is available in dataproviders.

dataprovider(dataset, data_format, **settings)[source]¶: Base dataprovider factory for all datatypes that returns the proper provider for the given data_format or raises a NoProviderAvailable.

validate(dataset, **kwd)[source]¶

base_dataprovider(dataset, **settings)[source]¶

chunk_dataprovider(dataset, **settings)[source]¶

chunk64_dataprovider(dataset, **settings)[source]¶

dataproviders = {'base': <function Data.base_dataprovider>, 'chunk': <function Data.chunk_dataprovider>, 'chunk64': <function Data.chunk64_dataprovider>}¶

class galaxy.datatypes.data.Text(**kwd)[source]¶

Bases: galaxy.datatypes.data.Data

edam_format = 'format_2330'¶

file_ext = 'txt'¶

line_class = 'line'¶

is_binary = False¶

get_mime()[source]¶: Returns the mime type of the datatype

set_meta(dataset, **kwd)[source]¶: Set the number of lines of data in dataset.

estimate_file_lines(dataset)[source]¶: Perform a rough estimate by extrapolating number of lines from a small read.

count_data_lines(dataset)[source]¶: Count the number of lines of data in dataset, skipping all blank lines and comments.

set_peek(dataset, line_count=None, is_multi_byte=False, WIDTH=256, skipchars=None, line_wrap=True, **kwd)[source]¶: Set the peek. This method is used by various subclasses of Text.

classmethod split(input_datasets, subdir_generator_function, split_params)[source]¶: Split the input files by line.

line_dataprovider(dataset, **settings)[source]¶: Returns an iterator over the dataset’s lines (that have been stripped) optionally excluding blank lines and lines that start with a comment character.

regex_line_dataprovider(dataset, **settings)[source]¶: Returns an iterator over the dataset’s lines optionally including/excluding lines that match one or more regex filters.

dataproviders = {'base': <function Data.base_dataprovider>, 'chunk': <function Data.chunk_dataprovider>, 'chunk64': <function Data.chunk64_dataprovider>, 'line': <function Text.line_dataprovider>, 'regex-line': <function Text.regex_line_dataprovider>}¶

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.data.Directory(**kwd)[source]¶

Bases: galaxy.datatypes.data.Data

Class representing a directory of files.

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.data.GenericAsn1(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

Class for generic ASN.1 text format

edam_data = 'data_0849'¶

edam_format = 'format_1966'¶

file_ext = 'asn1'¶

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.data.LineCount(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

Dataset contains a single line with a single integer that denotes the line count for a related dataset. Used for custom builds.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.data.Newick(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

New Hampshire/Newick Format

edam_data = 'data_0872'¶

edam_format = 'format_1910'¶

file_ext = 'newick'¶

sniff(filename)[source]¶: Returning false as the newick format is too general and cannot be sniffed.

get_visualizations(dataset)[source]¶: Returns a list of visualizations for datatype.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.data.Nexus(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

Nexus format as used By Paup, Mr Bayes, etc

edam_data = 'data_0872'¶

edam_format = 'format_1912'¶

file_ext = 'nex'¶

sniff_prefix(file_prefix)[source]¶: All Nexus Files Simply puts a ‘#NEXUS’ in its first line

get_visualizations(dataset)[source]¶: Returns a list of visualizations for datatype.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

galaxy.datatypes.data.get_test_fname(fname)[source]¶: Returns test data filename

galaxy.datatypes.data.get_file_peek(file_name, is_multi_byte=False, WIDTH=256, LINE_COUNT=5, skipchars=None, line_wrap=True)[source]¶

Returns the first LINE_COUNT lines wrapped to WIDTH.

Parameters: is_multi_byte (bool) – deprecated

>>> def assert_peek_is(file_name, expected, *args, **kwd):
...     path = get_test_fname(file_name)
...     peek = get_file_peek(path, *args, **kwd)
...     assert peek == expected, "%s != %s" % (peek, expected)
>>> assert_peek_is('0_nonewline', u'0')
>>> assert_peek_is('0.txt', u'0\n')
>>> assert_peek_is('4.bed', u'chr22\t30128507\t31828507\tuc003bnx.1_cds_2_0_chr22_29227_f\t0\t+\n', LINE_COUNT=1)
>>> assert_peek_is('1.bed', u'chr1\t147962192\t147962580\tCCDS989.1_cds_0_0_chr1_147962193_r\t0\t-\nchr1\t147984545\t147984630\tCCDS990.1_cds_0_0_chr1_147984546_f\t0\t+\n', LINE_COUNT=2)

galaxy.datatypes.genetics module¶

rgenetics datatypes Use at your peril Ross Lazarus for the rgenetics and galaxy projects

genome graphs datatypes derived from Interval datatypes genome graphs datasets have a header row with appropriate columnames The first column is always the marker - eg columname = rs, first row= rs12345 if the rows are snps subsequent row values are all numeric ! Will fail if any non numeric (eg ‘+’ or ‘NA’) values ross lazarus for rgenetics august 20 2007

class galaxy.datatypes.genetics.GenomeGraphs(**kwd)[source]¶

Bases: galaxy.datatypes.tabular.Tabular

Tab delimited data containing a marker id and any number of numeric values

file_ext = 'gg'¶

__init__(**kwd)[source]¶: Initialize gg datatype, by adding UCSC display apps

set_meta(dataset, **kwd)[source]¶

Tries to determine the number of columns as well as those columns that contain numerical values in the dataset. A skip parameter is used because various tabular data types reuse this function, and their data type classes are responsible to determine how many invalid comment lines should be skipped. Using None for skip will cause skip to be zero, but the first line will be processed as a header. A max_data_lines parameter is used because various tabular data types reuse this function, and their data type classes are responsible to determine how many data lines should be processed to ensure that the non-optional metadata parameters are properly set; if used, optional metadata parameters will be set to None, unless the entire file has already been read. Using None for max_data_lines will process all data lines.

Items of interest:

We treat ‘overwrite’ as always True (we always want to set tabular metadata when called).
If a tabular file has no data, it will have one column of type ‘str’.
We used to check only the first 100 lines when setting metadata and this class’s set_peek() method read the entire file to determine the number of lines in the file. Since metadata can now be processed on cluster nodes, we’ve merged the line count portion of the set_peek() processing here, and we now check the entire contents of the file.

as_ucsc_display_file(dataset, **kwd)[source]¶: Returns file

ucsc_links(dataset, type, app, base_url)[source]¶

from the ever-helpful angie hinrichs angie@soe.ucsc.edu a genome graphs call looks like this

http://genome.ucsc.edu/cgi-bin/hgGenome?clade=mammal&org=Human&db=hg18&hgGenome_dataSetName=dname &hgGenome_dataSetDescription=test&hgGenome_formatType=best%20guess&hgGenome_markerType=best%20guess &hgGenome_columnLabels=best%20guess&hgGenome_maxVal=&hgGenome_labelVals= &hgGenome_maxGapToFill=25000000&hgGenome_uploadFile=http://galaxy.esphealth.org/datasets/333/display/index &hgGenome_doSubmitUpload=submit

Galaxy gives this for an interval file

http://genome.ucsc.edu/cgi-bin/hgTracks?db=hg18&position=chr1:1-1000&hgt.customText= http%3A%2F%2Fgalaxy.esphealth.org%2Fdisplay_as%3Fid%3D339%26display_app%3Ducsc

make_html_table(dataset)[source]¶: Create HTML table, used for displaying peek

validate(dataset, **kwd)[source]¶: Validate a gg file - all numeric after header row

sniff_prefix(file_prefix)[source]¶

Determines whether the file is in gg format

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname( 'test_space.txt' )
>>> GenomeGraphs().sniff( fname )
False
>>> fname = get_test_fname( '1.gg' )
>>> GenomeGraphs().sniff( fname )
True

get_mime()[source]¶: Returns the mime type of the datatype

metadata_spec = {'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'markerCol': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.genetics.rgTabList(**kwd)[source]¶

Bases: galaxy.datatypes.tabular.Tabular

for sampleid and for featureid lists of exclusions or inclusions in the clean tool featureid subsets on statistical criteria -> specialized display such as gg

file_ext = 'rgTList'¶

__init__(**kwd)[source]¶: Initialize featurelistt datatype

display_peek(dataset)[source]¶: Returns formated html of peek

get_mime()[source]¶: Returns the mime type of the datatype

metadata_spec = {'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.rgSampleList(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.rgTabList

for sampleid exclusions or inclusions in the clean tool output from QC eg excess het, gender error, ibd pair member,eigen outlier,excess mendel errors,… since they can be uploaded, should be flexible but they are persistent at least same infrastructure for expression?

file_ext = 'rgSList'¶

__init__(**kwd)[source]¶: Initialize samplelist datatype

metadata_spec = {'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.rgFeatureList(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.rgTabList

for featureid lists of exclusions or inclusions in the clean tool output from QC eg low maf, high missingness, bad hwe in controls, excess mendel errors,… featureid subsets on statistical criteria -> specialized display such as gg same infrastructure for expression?

file_ext = 'rgFList'¶

__init__(**kwd)[source]¶: Initialize featurelist datatype

metadata_spec = {'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Rgenetics(**kwd)[source]¶

Bases: galaxy.datatypes.text.Html

base class to use for rgenetics datatypes derived from html - composite datatype elements stored in extra files path

composite_type: Optional[str] = 'auto_primary_file'¶

file_ext = 'rgenetics'¶

generate_primary_file(dataset=None)[source]¶

regenerate_primary_file(dataset)[source]¶: cannot do this until we are setting metadata

get_mime()[source]¶: Returns the mime type of the datatype

set_meta(dataset, **kwd)[source]¶: for lped/pbed eg

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.SNPMatrix(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.Rgenetics

BioC SNPMatrix Rgenetics data collections

file_ext = 'snpmatrix'¶

set_peek(dataset, **kwd)[source]¶: Set the peek. This method is used by various subclasses of Text.

sniff(filename)[source]¶: need to check the file header hex code

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Lped(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.Rgenetics

linkage pedigree (ped,map) Rgenetics data collections

file_ext = 'lped'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Pphe(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.Rgenetics

Plink phenotype file - header must have FID IID… Rgenetics data collections

file_ext = 'pphe'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Fphe(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.Rgenetics

fbat pedigree file - mad format with ! as first char on header row Rgenetics data collections

file_ext = 'fphe'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Phe(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.Rgenetics

Phenotype file

file_ext = 'phe'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Fped(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.Rgenetics

FBAT pedigree format - single file, map is header row of rs numbers. Strange. Rgenetics data collections

file_ext = 'fped'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Pbed(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.Rgenetics

Plink Binary compressed 2bit/geno Rgenetics data collections

file_ext = 'pbed'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.ldIndep(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.Rgenetics

LD (a good measure of redundancy of information) depleted Plink Binary compressed 2bit/geno This is really a plink binary, but some tools work better with less redundancy so are constrained to these files

file_ext = 'ldreduced'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Eigenstratgeno(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.Rgenetics

Eigenstrat format - may be able to get rid of this if we move to shellfish Rgenetics data collections

file_ext = 'eigenstratgeno'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Eigenstratpca(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.Rgenetics

Eigenstrat PCA file for case control adjustment Rgenetics data collections

file_ext = 'eigenstratpca'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Snptest(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.Rgenetics

BioC snptest Rgenetics data collections

file_ext = 'snptest'¶

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.IdeasPre(**kwd)[source]¶

Bases: galaxy.datatypes.text.Html

This datatype defines the input format required by IDEAS: https://academic.oup.com/nar/article/44/14/6721/2468150 The IDEAS preprocessor tool produces an output using this format. The extra_files_path of the primary input dataset contains the following files and directories. - chromosome_windows.txt (optional) - chromosomes.bed (optional) - IDEAS_input_config.txt - compressed archived tmp directory containing a number of compressed bed files.

composite_type: Optional[str] = 'auto_primary_file'¶

file_ext = 'ideaspre'¶

__init__(**kwd)[source]¶: Initialize the datatype

set_meta(dataset, **kwd)[source]¶: Set the number of lines of data in dataset.

generate_primary_file(dataset=None)[source]¶

regenerate_primary_file(dataset)[source]¶

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'chrom_bed': <galaxy.model.metadata.MetadataElementSpec object>, 'chrom_windows': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'input_config': <galaxy.model.metadata.MetadataElementSpec object>, 'tmp_archive': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Pheno(**kwd)[source]¶

Bases: galaxy.datatypes.tabular.Tabular

base class for pheno files

file_ext = 'pheno'¶

metadata_spec = {'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.RexpBase(**kwd)[source]¶

Bases: galaxy.datatypes.text.Html

base class for BioC data structures in Galaxy must be constructed with the pheno data in place since that goes into the metadata for each instance

file_ext = 'rexpbase'¶

html_table = None¶

composite_type: Optional[str] = 'auto_primary_file'¶

__init__(**kwd)[source]¶: Initialize the datatype

generate_primary_file(dataset=None)[source]¶: This is called only at upload to write the html file cannot rename the datasets here - they come with the default unfortunately

get_mime()[source]¶: Returns the mime type of the datatype

get_phecols(phenolist, maxConc=20)[source]¶: sept 2009: cannot use whitespace to split - make a more complex structure here and adjust the methods that rely on this structure return interesting phenotype column names for an rexpression eset or affybatch to use in array subsetting and so on. Returns a data structure for a dynamic Galaxy select parameter. A column with only 1 value doesn’t change, so is not interesting for analysis. A column with a different value in every row is equivalent to a unique identifier so is also not interesting for anova or limma analysis - both these are removed after the concordance (count of unique terms) is constructed for each column. Then a complication - each remaining pair of columns is tested for redundancy - if two columns are always paired, then only one is needed :)

get_pheno(dataset)[source]¶: expects a .pheno file in the extra_files_dir - ugh note that R is wierd and adds the row.name in the header so the columns are all wrong - unless you tell it not to. A file can be written as write.table(file=’foo.pheno’,pData(foo),sep=’ ‘,quote=F,row.names=F)

set_peek(dataset, **kwd)[source]¶: expects a .pheno file in the extra_files_dir - ugh note that R is weird and does not include the row.name in the header. why?

get_peek(dataset)[source]¶: expects a .pheno file in the extra_files_dir - ugh

get_file_peek(filename)[source]¶: can’t really peek at a filename - need the extra_files_path and such?

regenerate_primary_file(dataset)[source]¶: cannot do this until we are setting metadata

init_meta(dataset, copy_from=None)[source]¶

set_meta(dataset, **kwd)[source]¶: NOTE we apply the tabular machinary to the phenodata extracted from a BioC eSet or affybatch.

make_html_table(pp='nothing supplied from peek\n')[source]¶: Create HTML table, used for displaying peek

display_peek(dataset)[source]¶: Returns formatted html of peek

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'pheCols': <galaxy.model.metadata.MetadataElementSpec object>, 'pheno_path': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Affybatch(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.RexpBase

derived class for BioC data structures in Galaxy

file_ext = 'affybatch'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'pheCols': <galaxy.model.metadata.MetadataElementSpec object>, 'pheno_path': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.Eset(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.RexpBase

derived class for BioC data structures in Galaxy

file_ext = 'eset'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'pheCols': <galaxy.model.metadata.MetadataElementSpec object>, 'pheno_path': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.MAlist(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.RexpBase

derived class for BioC data structures in Galaxy

file_ext = 'malist'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'pheCols': <galaxy.model.metadata.MetadataElementSpec object>, 'pheno_path': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.LinkageStudies(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

superclass for classical linkage analysis suites

test_files = ['linkstudies.allegro_fparam', 'linkstudies.alohomora_gts', 'linkstudies.linkage_datain', 'linkstudies.linkage_map']¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.genetics.GenotypeMatrix(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.LinkageStudies

Sample matrix of genotypes - GTs as columns

file_ext = 'alohomora_gts'¶

__init__(**kwd)[source]¶: Initialize the datatype

header_check(fio)[source]¶

sniff_prefix(file_prefix)[source]¶

>>> classname = GenotypeMatrix
>>> from galaxy.datatypes.sniff import get_test_fname
>>> extn_true = classname().file_ext
>>> file_true = get_test_fname("linkstudies." + extn_true)
>>> classname().sniff(file_true)
True
>>> false_files = list(LinkageStudies.test_files)
>>> false_files.remove("linkstudies." + extn_true)
>>> result_true = []
>>> for fname in false_files:
...     file_false = get_test_fname(fname)
...     res = classname().sniff(file_false)
...     if res:
...         result_true.append(fname)
>>>
>>> result_true
[]

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.genetics.MarkerMap(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.LinkageStudies

Map of genetic markers including physical and genetic distance Common input format for linkage programs

chrom, genetic pos, markername, physical pos, Nr

file_ext = 'linkage_map'¶

header_check(fio)[source]¶

sniff_prefix(file_prefix)[source]¶

>>> classname = MarkerMap
>>> from galaxy.datatypes.sniff import get_test_fname
>>> extn_true = classname().file_ext
>>> file_true = get_test_fname("linkstudies." + extn_true)
>>> classname().sniff(file_true)
True
>>> false_files = list(LinkageStudies.test_files)
>>> false_files.remove("linkstudies." + extn_true)
>>> result_true = []
>>> for fname in false_files:
...     file_false = get_test_fname(fname)
...     res = classname().sniff(file_false)
...     if res:
...         result_true.append(fname)
>>>
>>> result_true
[]

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.genetics.DataIn(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.LinkageStudies

Common linkage input file for intermarker distances and recombination rates

file_ext = 'linkage_datain'¶

__init__(**kwd)[source]¶: Initialize the datatype

sniff_prefix(file_prefix)[source]¶

>>> classname = DataIn
>>> from galaxy.datatypes.sniff import get_test_fname
>>> extn_true = classname().file_ext
>>> file_true = get_test_fname("linkstudies." + extn_true)
>>> classname().sniff(file_true)
True
>>> false_files = list(LinkageStudies.test_files)
>>> false_files.remove("linkstudies." + extn_true)
>>> result_true = []
>>> for fname in false_files:
...     file_false = get_test_fname(fname)
...     res = classname().sniff(file_false)
...     if res:
...         result_true.append(fname)
>>>
>>> result_true
[]

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.genetics.AllegroLOD(**kwd)[source]¶

Bases: galaxy.datatypes.genetics.LinkageStudies

Allegro output format for LOD scores

file_ext = 'allegro_fparam'¶

header_check(fio)[source]¶

sniff_prefix(file_prefix)[source]¶

>>> classname = AllegroLOD
>>> from galaxy.datatypes.sniff import get_test_fname
>>> extn_true = classname().file_ext
>>> file_true = get_test_fname("linkstudies." + extn_true)
>>> classname().sniff(file_true)
True
>>> false_files = list(LinkageStudies.test_files)
>>> false_files.remove("linkstudies." + extn_true)
>>> result_true = []
>>> for fname in false_files:
...     file_false = get_test_fname(fname)
...     res = classname().sniff(file_false)
...     if res:
...         result_true.append(fname)
>>>
>>> result_true
[]

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

galaxy.datatypes.gis module¶

GIS classes

class galaxy.datatypes.gis.Shapefile(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

The Shapefile data format: For more information please see http://en.wikipedia.org/wiki/Shapefile

composite_type: Optional[str] = 'auto_primary_file'¶

file_ext = 'shp'¶

__init__(**kwd)[source]¶: Initialize the datatype

generate_primary_file(dataset=None)[source]¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text.

display_peek(dataset)[source]¶: Create HTML content, used for displaying peek.

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.graph module¶

Graph content classes.

class galaxy.datatypes.graph.Xgmml(**kwd)[source]¶

Bases: galaxy.datatypes.xml.GenericXml

XGMML graph format (http://wiki.cytoscape.org/Cytoscape_User_Manual/Network_Formats).

file_ext = 'xgmml'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

sniff(filename)[source]¶: Returns false and the user must manually set.

static merge(split_files, output_file)[source]¶: Merging multiple XML files is non-trivial and must be done in subclasses.

node_edge_dataprovider(dataset, **settings)[source]¶

dataproviders = {'base': <function Data.base_dataprovider>, 'chunk': <function Data.chunk_dataprovider>, 'chunk64': <function Data.chunk64_dataprovider>, 'line': <function Text.line_dataprovider>, 'node-edge': <function Xgmml.node_edge_dataprovider>, 'regex-line': <function Text.regex_line_dataprovider>, 'xml': <function GenericXml.xml_dataprovider>}¶

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.graph.Sif(**kwd)[source]¶

Bases: galaxy.datatypes.tabular.Tabular

SIF graph format (http://wiki.cytoscape.org/Cytoscape_User_Manual/Network_Formats).

First column: node id Second column: relationship type Third to Nth column: target ids for link

file_ext = 'sif'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text

sniff(filename)[source]¶: Returns false and the user must manually set.

static merge(split_files, output_file)[source]¶: Merge files with copy.copyfileobj() will not hit the max argument limitation of cat. gz and bz2 files are also working.

node_edge_dataprovider(dataset, **settings)[source]¶

dataproviders = {'base': <function Data.base_dataprovider>, 'chunk': <function Data.chunk_dataprovider>, 'chunk64': <function Data.chunk64_dataprovider>, 'column': <function TabularData.column_dataprovider>, 'dataset-column': <function TabularData.dataset_column_dataprovider>, 'dataset-dict': <function TabularData.dataset_dict_dataprovider>, 'dict': <function TabularData.dict_dataprovider>, 'line': <function Text.line_dataprovider>, 'node-edge': <function Sif.node_edge_dataprovider>, 'regex-line': <function Text.regex_line_dataprovider>}¶

metadata_spec = {'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.graph.XGMMLGraphDataProvider(source, selector=None, max_depth=None, **kwargs)[source]¶

Bases: galaxy.datatypes.dataproviders.hierarchy.XMLDataProvider

Provide two lists: nodes, edges:

'nodes': contains objects of the form:
    { 'id' : <some string id>, 'data': <any extra data> }
'edges': contains objects of the form:
    { 'source' : <an index into nodes>, 'target': <an index into nodes>, 'data': <any extra data> }

settings: Dict[str, str] = {'limit': 'int', 'max_depth': 'int', 'offset': 'int', 'selector': 'str'}¶

class galaxy.datatypes.graph.SIFGraphDataProvider(source, indeces=None, column_count=None, column_types=None, parsers=None, parse_columns=True, deliminator='\t', filters=None, **kwargs)[source]¶

Bases: galaxy.datatypes.dataproviders.column.ColumnarDataProvider

Provide two lists: nodes, edges:

'nodes': contains objects of the form:
    { 'id' : <some string id>, 'data': <any extra data> }
'edges': contains objects of the form:
    { 'source' : <an index into nodes>, 'target': <an index into nodes>, 'data': <any extra data> }

settings: Dict[str, str] = {'column_count': 'int', 'column_types': 'list:str', 'comment_char': 'str', 'deliminator': 'str', 'filters': 'list:str', 'indeces': 'list:int', 'invert': 'bool', 'limit': 'int', 'offset': 'int', 'parse_columns': 'bool', 'provide_blank': 'bool', 'regex_list': 'list:escaped', 'strip_lines': 'bool', 'strip_newlines': 'bool'}¶

galaxy.datatypes.images module¶

Image classes

class galaxy.datatypes.images.Image(**kwd)[source]¶

Bases: galaxy.datatypes.data.Data

Class describing an image

edam_data = 'data_2968'¶

edam_format = 'format_3547'¶

file_ext = ''¶

__init__(**kwd)[source]¶: Initialize the datatype

set_peek(dataset, is_multi_byte=False)[source]¶

Set the peek and blurb text

Parameters: is_multi_byte (bool) – deprecated

sniff(filename)[source]¶: Determine if the file is in this format

handle_dataset_as_image(hda)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Jpg(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3579'¶

file_ext = 'jpg'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Png(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3603'¶

file_ext = 'png'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Tiff(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3591'¶

file_ext = 'tiff'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Hamamatsu(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

file_ext = 'vms'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Mirax(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

file_ext = 'mrxs'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Sakura(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

file_ext = 'svslide'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Nrrd(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

file_ext = 'nrrd'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Bmp(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3592'¶

file_ext = 'bmp'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Gif(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3467'¶

file_ext = 'gif'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Im(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3593'¶

file_ext = 'im'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Pcd(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3594'¶

file_ext = 'pcd'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Pcx(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3595'¶

file_ext = 'pcx'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Ppm(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3596'¶

file_ext = 'ppm'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Psd(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3597'¶

file_ext = 'psd'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Xbm(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3598'¶

file_ext = 'xbm'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Xpm(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3599'¶

file_ext = 'xpm'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Rgb(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3600'¶

file_ext = 'rgb'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Pbm(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3601'¶

file_ext = 'pbm'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Pgm(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3602'¶

file_ext = 'pgm'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Eps(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3466'¶

file_ext = 'eps'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Rast(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3605'¶

file_ext = 'rast'¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Pdf(**kwd)[source]¶

Bases: galaxy.datatypes.images.Image

edam_format = 'format_3508'¶

file_ext = 'pdf'¶

sniff(filename)[source]¶: Determine if the file is in pdf format.

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.images.create_applet_tag_peek(class_name, archive, params)[source]¶

class galaxy.datatypes.images.Tck(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Tracks file format (.tck) format https://mrtrix.readthedocs.io/en/latest/getting_started/image_data.html#tracks-file-format-tck

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('fibers_sparse_top_6_lines.tck')
>>> Tck().sniff( fname )
True
>>> fname = get_test_fname('2.txt')
>>> Tck().sniff( fname )
False

file_ext = 'tck'¶

sniff_prefix(file_prefix)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.images.Trk(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Track File format (.trk) is the tractography file format. http://trackvis.org/docs/?subsect=fileformat

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('IIT2mean_top_2000bytes.trk')
>>> Trk().sniff( fname )
True
>>> fname = get_test_fname('2.txt')
>>> Trk().sniff( fname )
False

file_ext = 'trk'¶

sniff_prefix(file_prefix)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.images.Gmaj(**kwd)[source]¶

Bases: galaxy.datatypes.data.Data

Class describing a GMAJ Applet

edam_format = 'format_3547'¶

file_ext = 'gmaj.zip'¶

copy_safe_peek = False¶

set_peek(dataset, is_multi_byte=False)[source]¶

Set the peek and blurb text

Parameters: is_multi_byte (bool) – deprecated

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

get_mime()[source]¶: Returns the mime type of the datatype

sniff(filename)[source]¶: NOTE: the sniff.convert_newlines() call in the upload utility will keep Gmaj data types from being correctly sniffed, but the files can be uploaded (they’ll be sniffed as ‘txt’). This sniff function is here to provide an example of a sniffer for a zip file.

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Analyze75(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Mayo Analyze 7.5 files http://www.imzml.org

file_ext = 'analyze75'¶

composite_type: Optional[str] = 'auto_primary_file'¶

__init__(**kwd)[source]¶: Initialize the datatype

generate_primary_file(dataset=None)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Nifti1(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Nifti1 format https://nifti.nimh.nih.gov/pub/dist/src/niftilib/nifti1.h

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('T1_top_350bytes.nii1')
>>> Nifti1().sniff( fname )
True
>>> fname = get_test_fname('2.txt')
>>> Nifti1().sniff( fname )
False

file_ext = 'nii1'¶

sniff_prefix(file_prefix)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.images.Nifti2(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

Nifti2 format https://brainder.org/2015/04/03/the-nifti-2-file-format/

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('avg152T1_LR_nifti2_top_100bytes.nii2')
>>> Nifti2().sniff( fname )
True
>>> fname = get_test_fname('T1_top_350bytes.nii1')
>>> Nifti2().sniff( fname )
False

file_ext = 'nii2'¶

sniff_prefix(file_prefix)[source]¶

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.images.Gifti(**kwd)[source]¶

Bases: galaxy.datatypes.xml.GenericXml

Class describing a Gifti format

file_ext = 'gii'¶

sniff_prefix(file_prefix)[source]¶

Determines whether the file is a Gifti file

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('Human.colin.R.activations.label.gii')
>>> Gifti().sniff(fname)
True
>>> fname = get_test_fname('interval.interval')
>>> Gifti().sniff(fname)
False
>>> fname = get_test_fname('megablast_xml_parser_test1.blastxml')
>>> Gifti().sniff(fname)
False
>>> fname = get_test_fname('tblastn_four_human_vs_rhodopsin.blastxml')
>>> Gifti().sniff(fname)
False

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.images.Html(**kwd)[source]¶

Bases: galaxy.datatypes.text.Html

Deprecated class. This class should not be used anymore, but the galaxy.datatypes.text:Html one. This is for backwards compatibilities only.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.images.Laj(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

Class describing a LAJ Applet

file_ext = 'laj'¶

copy_safe_peek = False¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek. This method is used by various subclasses of Text.

display_peek(dataset)[source]¶: Create HTML table, used for displaying peek

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.interval module¶

Interval datatypes

class galaxy.datatypes.interval.Interval(**kwd)[source]¶

Bases: galaxy.datatypes.tabular.Tabular

Tab delimited data containing interval information

edam_data = 'data_3002'¶

edam_format = 'format_3475'¶

file_ext = 'interval'¶

line_class = 'region'¶

track_type: Optional[str] = 'FeatureTrack'¶

data_sources: Dict[str, str] = {'data': 'tabix', 'index': 'bigwig'}¶: Add metadata elements

__init__(**kwd)[source]¶: Initialize interval datatype, by adding UCSC display apps

init_meta(dataset, copy_from=None)[source]¶

set_meta(dataset, overwrite=True, first_line_is_header=False, **kwd)[source]¶: Tries to guess from the line the location number of the column for the chromosome, region start-end and strand

displayable(dataset)[source]¶

get_estimated_display_viewport(dataset, chrom_col=None, start_col=None, end_col=None)[source]¶: Return a chrom, start, stop tuple for viewing a file.

as_ucsc_display_file(dataset, **kwd)[source]¶: Returns file contents with only the bed data

display_peek(dataset)[source]¶: Returns formated html of peek

ucsc_links(dataset, type, app, base_url)[source]¶: Generate links to UCSC genome browser sites based on the dbkey and content of dataset.

validate(dataset, **kwd)[source]¶: Validate an interval file using the bx GenomicIntervalReader

repair_methods(dataset)[source]¶: Return options for removing errors along with a description

sniff_prefix(file_prefix)[source]¶

Checks for ‘intervalness’

This format is mostly used by galaxy itself. Valid interval files should include a valid header comment, but this seems to be loosely regulated.

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname( 'test_space.txt' )
>>> Interval().sniff( fname )
False
>>> fname = get_test_fname( 'interval.interval' )
>>> Interval().sniff( fname )
True

get_track_resolution(dataset, start, end)[source]¶

genomic_region_dataprovider(dataset, **settings)[source]¶

genomic_region_dict_dataprovider(dataset, **settings)[source]¶

interval_dataprovider(dataset, **settings)[source]¶

interval_dict_dataprovider(dataset, **settings)[source]¶

dataproviders = {'base': <function Data.base_dataprovider>, 'chunk': <function Data.chunk_dataprovider>, 'chunk64': <function Data.chunk64_dataprovider>, 'column': <function TabularData.column_dataprovider>, 'dataset-column': <function TabularData.dataset_column_dataprovider>, 'dataset-dict': <function TabularData.dataset_dict_dataprovider>, 'dict': <function TabularData.dict_dataprovider>, 'genomic-region': <function Interval.genomic_region_dataprovider>, 'genomic-region-dict': <function Interval.genomic_region_dict_dataprovider>, 'interval': <function Interval.interval_dataprovider>, 'interval-dict': <function Interval.interval_dict_dataprovider>, 'line': <function Text.line_dataprovider>, 'regex-line': <function Text.regex_line_dataprovider>}¶

metadata_spec = {'chromCol': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'endCol': <galaxy.model.metadata.MetadataElementSpec object>, 'nameCol': <galaxy.model.metadata.MetadataElementSpec object>, 'startCol': <galaxy.model.metadata.MetadataElementSpec object>, 'strandCol': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.interval.BedGraph(**kwd)[source]¶

Bases: galaxy.datatypes.interval.Interval

Tab delimited chrom/start/end/datavalue dataset

edam_format = 'format_3583'¶

file_ext = 'bedgraph'¶

track_type: Optional[str] = 'LineTrack'¶

data_sources: Dict[str, str] = {'data': 'bigwig', 'index': 'bigwig'}¶

as_ucsc_display_file(dataset, **kwd)[source]¶: Returns file contents as is with no modifications. TODO: this is a functional stub and will need to be enhanced moving forward to provide additional support for bedgraph.

get_estimated_display_viewport(dataset, chrom_col=0, start_col=1, end_col=2)[source]¶: Set viewport based on dataset’s first 100 lines.

metadata_spec = {'chromCol': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'endCol': <galaxy.model.metadata.MetadataElementSpec object>, 'nameCol': <galaxy.model.metadata.MetadataElementSpec object>, 'startCol': <galaxy.model.metadata.MetadataElementSpec object>, 'strandCol': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.interval.Bed(**kwd)[source]¶

Bases: galaxy.datatypes.interval.Interval

Tab delimited data in BED format

edam_format = 'format_3003'¶

file_ext = 'bed'¶

data_sources: Dict[str, str] = {'data': 'tabix', 'feature_search': 'fli', 'index': 'bigwig'}¶

track_type: Optional[str] = 'FeatureTrack'¶

column_names = ['Chrom', 'Start', 'End', 'Name', 'Score', 'Strand', 'ThickStart', 'ThickEnd', 'ItemRGB', 'BlockCount', 'BlockSizes', 'BlockStarts']¶: Add metadata elements

set_meta(dataset, overwrite=True, **kwd)[source]¶: Sets the metadata information for datasets previously determined to be in bed format.

as_ucsc_display_file(dataset, **kwd)[source]¶: Returns file contents with only the bed data. If bed 6+, treat as interval.

sniff_prefix(file_prefix)[source]¶

Checks for ‘bedness’

BED lines have three required fields and nine additional optional fields. The number of fields per line must be consistent throughout any single set of data in an annotation track. The order of the optional fields is binding: lower-numbered fields must always be populated if higher-numbered fields are used. The data type of all 12 columns is: 1-str, 2-int, 3-int, 4-str, 5-int, 6-str, 7-int, 8-int, 9-int or list, 10-int, 11-list, 12-list

For complete details see http://genome.ucsc.edu/FAQ/FAQformat#format1

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname( 'test_tab.bed' )
>>> Bed().sniff( fname )
True
>>> fname = get_test_fname( 'interv1.bed' )
>>> Bed().sniff( fname )
True
>>> fname = get_test_fname( 'complete.bed' )
>>> Bed().sniff( fname )
True

metadata_spec = {'chromCol': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'endCol': <galaxy.model.metadata.MetadataElementSpec object>, 'nameCol': <galaxy.model.metadata.MetadataElementSpec object>, 'startCol': <galaxy.model.metadata.MetadataElementSpec object>, 'strandCol': <galaxy.model.metadata.MetadataElementSpec object>, 'viz_filter_cols': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.interval.ProBed(**kwd)[source]¶

Bases: galaxy.datatypes.interval.Bed

Tab delimited data in proBED format - adaptation of BED for proteomics data.

edam_format = 'format_3827'¶

file_ext = 'probed'¶

column_names = ['Chrom', 'Start', 'End', 'Name', 'Score', 'Strand', 'ThickStart', 'ThickEnd', 'ItemRGB', 'BlockCount', 'BlockSizes', 'BlockStarts', 'ProteinAccession', 'PeptideSequence', 'Uniqueness', 'GenomeReferenceVersion', 'PsmScore', 'Fdr', 'Modifications', 'Charge', 'ExpMassToCharge', 'CalcMassToCharge', 'PsmRank', 'DatasetID', 'Uri']¶

metadata_spec = {'chromCol': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'endCol': <galaxy.model.metadata.MetadataElementSpec object>, 'nameCol': <galaxy.model.metadata.MetadataElementSpec object>, 'startCol': <galaxy.model.metadata.MetadataElementSpec object>, 'strandCol': <galaxy.model.metadata.MetadataElementSpec object>, 'viz_filter_cols': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.interval.BedStrict(**kwd)[source]¶

Bases: galaxy.datatypes.interval.Bed

Tab delimited data in strict BED format - no non-standard columns allowed

edam_format = 'format_3584'¶

file_ext = 'bedstrict'¶

allow_datatype_change: Optional[bool] = False¶

__init__(**kwd)[source]¶: Initialize interval datatype, by adding UCSC display apps

set_meta(dataset, overwrite=True, **kwd)[source]¶: Sets the metadata information for datasets previously determined to be in bed format.

sniff(filename)[source]¶

metadata_spec = {'chromCol': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'endCol': <galaxy.model.metadata.MetadataElementSpec object>, 'nameCol': <galaxy.model.metadata.MetadataElementSpec object>, 'startCol': <galaxy.model.metadata.MetadataElementSpec object>, 'strandCol': <galaxy.model.metadata.MetadataElementSpec object>, 'viz_filter_cols': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.interval.Bed6(**kwd)[source]¶

Bases: galaxy.datatypes.interval.BedStrict

Tab delimited data in strict BED format - no non-standard columns allowed; column count forced to 6

edam_format = 'format_3585'¶

file_ext = 'bed6'¶

metadata_spec = {'chromCol': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'endCol': <galaxy.model.metadata.MetadataElementSpec object>, 'nameCol': <galaxy.model.metadata.MetadataElementSpec object>, 'startCol': <galaxy.model.metadata.MetadataElementSpec object>, 'strandCol': <galaxy.model.metadata.MetadataElementSpec object>, 'viz_filter_cols': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.interval.Bed12(**kwd)[source]¶

Bases: galaxy.datatypes.interval.BedStrict

Tab delimited data in strict BED format - no non-standard columns allowed; column count forced to 12

edam_format = 'format_3586'¶

file_ext = 'bed12'¶

metadata_spec = {'chromCol': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'endCol': <galaxy.model.metadata.MetadataElementSpec object>, 'nameCol': <galaxy.model.metadata.MetadataElementSpec object>, 'startCol': <galaxy.model.metadata.MetadataElementSpec object>, 'strandCol': <galaxy.model.metadata.MetadataElementSpec object>, 'viz_filter_cols': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.interval.Gff(**kwd)[source]¶

Bases: galaxy.datatypes.tabular.Tabular, galaxy.datatypes.interval._RemoteCallMixin

Tab delimited data in Gff format

edam_data = 'data_1255'¶

edam_format = 'format_2305'¶

file_ext = 'gff'¶

valid_gff_frame = ['.', '0', '1', '2']¶

column_names = ['Seqname', 'Source', 'Feature', 'Start', 'End', 'Score', 'Strand', 'Frame', 'Group']¶

data_sources: Dict[str, str] = {'data': 'interval_index', 'feature_search': 'fli', 'index': 'bigwig'}¶

track_type: Optional[str] = 'FeatureTrack'¶: Add metadata elements

__init__(**kwd)[source]¶: Initialize datatype, by adding GBrowse display app

set_attribute_metadata(dataset)[source]¶: Sets metadata elements for dataset’s attributes.

set_meta(dataset, overwrite=True, **kwd)[source]¶

Tries to determine the number of columns as well as those columns that contain numerical values in the dataset. A skip parameter is used because various tabular data types reuse this function, and their data type classes are responsible to determine how many invalid comment lines should be skipped. Using None for skip will cause skip to be zero, but the first line will be processed as a header. A max_data_lines parameter is used because various tabular data types reuse this function, and their data type classes are responsible to determine how many data lines should be processed to ensure that the non-optional metadata parameters are properly set; if used, optional metadata parameters will be set to None, unless the entire file has already been read. Using None for max_data_lines will process all data lines.

Items of interest:

We treat ‘overwrite’ as always True (we always want to set tabular metadata when called).
If a tabular file has no data, it will have one column of type ‘str’.
We used to check only the first 100 lines when setting metadata and this class’s set_peek() method read the entire file to determine the number of lines in the file. Since metadata can now be processed on cluster nodes, we’ve merged the line count portion of the set_peek() processing here, and we now check the entire contents of the file.

display_peek(dataset)[source]¶: Returns formated html of peek

get_estimated_display_viewport(dataset)[source]¶: Return a chrom, start, stop tuple for viewing a file. There are slight differences between gff 2 and gff 3 formats. This function should correctly handle both…

ucsc_links(dataset, type, app, base_url)[source]¶

gbrowse_links(dataset, type, app, base_url)[source]¶

sniff_prefix(file_prefix)[source]¶

Determines whether the file is in gff format

GFF lines have nine required fields that must be tab-separated.

For complete details see http://genome.ucsc.edu/FAQ/FAQformat#format3

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('gff.gff3')
>>> Gff().sniff( fname )
False
>>> fname = get_test_fname('test.gff')
>>> Gff().sniff( fname )
True

genomic_region_dataprovider(dataset, **settings)[source]¶

genomic_region_dict_dataprovider(dataset, **settings)[source]¶

interval_dataprovider(dataset, **settings)[source]¶

interval_dict_dataprovider(dataset, **settings)[source]¶

dataproviders = {'base': <function Data.base_dataprovider>, 'chunk': <function Data.chunk_dataprovider>, 'chunk64': <function Data.chunk64_dataprovider>, 'column': <function TabularData.column_dataprovider>, 'dataset-column': <function TabularData.dataset_column_dataprovider>, 'dataset-dict': <function TabularData.dataset_dict_dataprovider>, 'dict': <function TabularData.dict_dataprovider>, 'genomic-region': <function Gff.genomic_region_dataprovider>, 'genomic-region-dict': <function Gff.genomic_region_dict_dataprovider>, 'interval': <function Gff.interval_dataprovider>, 'interval-dict': <function Gff.interval_dict_dataprovider>, 'line': <function Text.line_dataprovider>, 'regex-line': <function Text.regex_line_dataprovider>}¶

metadata_spec = {'attribute_types': <galaxy.model.metadata.MetadataElementSpec object>, 'attributes': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.interval.Gff3(**kwd)[source]¶

Bases: galaxy.datatypes.interval.Gff

Tab delimited data in Gff3 format

edam_format = 'format_1975'¶

file_ext = 'gff3'¶

valid_gff3_strand = ['+', '-', '.', '?']¶

valid_gff3_phase = ['.', '0', '1', '2']¶

column_names = ['Seqid', 'Source', 'Type', 'Start', 'End', 'Score', 'Strand', 'Phase', 'Attributes']¶

track_type: Optional[str] = 'FeatureTrack'¶: Add metadata elements

__init__(**kwd)[source]¶: Initialize datatype, by adding GBrowse display app

set_meta(dataset, overwrite=True, **kwd)[source]¶

Tries to determine the number of columns as well as those columns that contain numerical values in the dataset. A skip parameter is used because various tabular data types reuse this function, and their data type classes are responsible to determine how many invalid comment lines should be skipped. Using None for skip will cause skip to be zero, but the first line will be processed as a header. A max_data_lines parameter is used because various tabular data types reuse this function, and their data type classes are responsible to determine how many data lines should be processed to ensure that the non-optional metadata parameters are properly set; if used, optional metadata parameters will be set to None, unless the entire file has already been read. Using None for max_data_lines will process all data lines.

Items of interest:

We treat ‘overwrite’ as always True (we always want to set tabular metadata when called).
If a tabular file has no data, it will have one column of type ‘str’.
We used to check only the first 100 lines when setting metadata and this class’s set_peek() method read the entire file to determine the number of lines in the file. Since metadata can now be processed on cluster nodes, we’ve merged the line count portion of the set_peek() processing here, and we now check the entire contents of the file.

sniff_prefix(file_prefix)[source]¶

Determines whether the file is in GFF version 3 format

GFF 3 format:

adds a mechanism for representing more than one level of hierarchical grouping of features and subfeatures.
separates the ideas of group membership and feature name/id
constrains the feature type field to be taken from a controlled vocabulary.
allows a single feature, such as an exon, to belong to more than one group at a time.
provides an explicit convention for pairwise alignments
provides an explicit convention for features that occupy disjunct regions

The format consists of 9 columns, separated by tabs (NOT spaces).

Undefined fields are replaced with the “.” character, as described in the original GFF spec.

For complete details see http://song.sourceforge.net/gff3.shtml

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname( 'test.gff' )
>>> Gff3().sniff( fname )
False
>>> fname = get_test_fname( 'test.gtf' )
>>> Gff3().sniff( fname )
False
>>> fname = get_test_fname('gff.gff3')
>>> Gff3().sniff( fname )
True
>>> fname = get_test_fname( 'grch37.75.gtf' )
>>> Gff3().sniff( fname )
False

metadata_spec = {'attribute_types': <galaxy.model.metadata.MetadataElementSpec object>, 'attributes': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.interval.Gtf(**kwd)[source]¶

Bases: galaxy.datatypes.interval.Gff

Tab delimited data in Gtf format

edam_format = 'format_2306'¶

file_ext = 'gtf'¶

column_names = ['Seqname', 'Source', 'Feature', 'Start', 'End', 'Score', 'Strand', 'Frame', 'Attributes']¶

track_type: Optional[str] = 'FeatureTrack'¶: Add metadata elements

sniff_prefix(file_prefix)[source]¶

Determines whether the file is in gtf format

GTF lines have nine required fields that must be tab-separated. The first eight GTF fields are the same as GFF. The group field has been expanded into a list of attributes. Each attribute consists of a type/value pair. Attributes must end in a semi-colon, and be separated from any following attribute by exactly one space. The attribute list must begin with the two mandatory attributes:

gene_id value - A globally unique identifier for the genomic source of the sequence. transcript_id value - A globally unique identifier for the predicted transcript.

For complete details see http://genome.ucsc.edu/FAQ/FAQformat#format4

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname( '1.bed' )
>>> Gtf().sniff( fname )
False
>>> fname = get_test_fname( 'test.gff' )
>>> Gtf().sniff( fname )
False
>>> fname = get_test_fname( 'test.gtf' )
>>> Gtf().sniff( fname )
True
>>> fname = get_test_fname( 'grch37.75.gtf' )
>>> Gtf().sniff( fname )
True

metadata_spec = {'attribute_types': <galaxy.model.metadata.MetadataElementSpec object>, 'attributes': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.interval.Wiggle(**kwd)[source]¶

Bases: galaxy.datatypes.tabular.Tabular, galaxy.datatypes.interval._RemoteCallMixin

Tab delimited data in wiggle format

edam_format = 'format_3005'¶

file_ext = 'wig'¶

track_type: Optional[str] = 'LineTrack'¶

data_sources: Dict[str, str] = {'data': 'bigwig', 'index': 'bigwig'}¶

__init__(**kwd)[source]¶: Initialize the datatype

get_estimated_display_viewport(dataset)[source]¶: Return a chrom, start, stop tuple for viewing a file.

gbrowse_links(dataset, type, app, base_url)[source]¶

ucsc_links(dataset, type, app, base_url)[source]¶

display_peek(dataset)[source]¶: Returns formated html of peek

set_meta(dataset, overwrite=True, **kwd)[source]¶

Tries to determine the number of columns as well as those columns that contain numerical values in the dataset. A skip parameter is used because various tabular data types reuse this function, and their data type classes are responsible to determine how many invalid comment lines should be skipped. Using None for skip will cause skip to be zero, but the first line will be processed as a header. A max_data_lines parameter is used because various tabular data types reuse this function, and their data type classes are responsible to determine how many data lines should be processed to ensure that the non-optional metadata parameters are properly set; if used, optional metadata parameters will be set to None, unless the entire file has already been read. Using None for max_data_lines will process all data lines.

Items of interest:

We treat ‘overwrite’ as always True (we always want to set tabular metadata when called).
If a tabular file has no data, it will have one column of type ‘str’.
We used to check only the first 100 lines when setting metadata and this class’s set_peek() method read the entire file to determine the number of lines in the file. Since metadata can now be processed on cluster nodes, we’ve merged the line count portion of the set_peek() processing here, and we now check the entire contents of the file.

sniff_prefix(file_prefix)[source]¶

Determines wether the file is in wiggle format

The .wig format is line-oriented. Wiggle data is preceeded by a track definition line, which adds a number of options for controlling the default display of this track. Following the track definition line is the track data, which can be entered in several different formats.

The track definition line begins with the word ‘track’ followed by the track type. The track type with version is REQUIRED, and it currently must be wiggle_0. For example, track type=wiggle_0…

For complete details see http://genome.ucsc.edu/goldenPath/help/wiggle.html

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname( 'interv1.bed' )
>>> Wiggle().sniff( fname )
False
>>> fname = get_test_fname( 'wiggle.wig' )
>>> Wiggle().sniff( fname )
True

get_track_resolution(dataset, start, end)[source]¶

wiggle_dataprovider(dataset, **settings)[source]¶

wiggle_dict_dataprovider(dataset, **settings)[source]¶

dataproviders = {'base': <function Data.base_dataprovider>, 'chunk': <function Data.chunk_dataprovider>, 'chunk64': <function Data.chunk64_dataprovider>, 'column': <function TabularData.column_dataprovider>, 'dataset-column': <function TabularData.dataset_column_dataprovider>, 'dataset-dict': <function TabularData.dataset_dict_dataprovider>, 'dict': <function TabularData.dict_dataprovider>, 'line': <function Text.line_dataprovider>, 'regex-line': <function Text.regex_line_dataprovider>, 'wiggle': <function Wiggle.wiggle_dataprovider>, 'wiggle-dict': <function Wiggle.wiggle_dict_dataprovider>}¶

metadata_spec = {'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.interval.CustomTrack(**kwd)[source]¶

Bases: galaxy.datatypes.tabular.Tabular

UCSC CustomTrack

edam_format = 'format_3588'¶

file_ext = 'customtrack'¶

__init__(**kwd)[source]¶: Initialize interval datatype, by adding UCSC display app

set_meta(dataset, overwrite=True, **kwd)[source]¶

Tries to determine the number of columns as well as those columns that contain numerical values in the dataset. A skip parameter is used because various tabular data types reuse this function, and their data type classes are responsible to determine how many invalid comment lines should be skipped. Using None for skip will cause skip to be zero, but the first line will be processed as a header. A max_data_lines parameter is used because various tabular data types reuse this function, and their data type classes are responsible to determine how many data lines should be processed to ensure that the non-optional metadata parameters are properly set; if used, optional metadata parameters will be set to None, unless the entire file has already been read. Using None for max_data_lines will process all data lines.

Items of interest:

We treat ‘overwrite’ as always True (we always want to set tabular metadata when called).
If a tabular file has no data, it will have one column of type ‘str’.
We used to check only the first 100 lines when setting metadata and this class’s set_peek() method read the entire file to determine the number of lines in the file. Since metadata can now be processed on cluster nodes, we’ve merged the line count portion of the set_peek() processing here, and we now check the entire contents of the file.

display_peek(dataset)[source]¶: Returns formated html of peek

get_estimated_display_viewport(dataset, chrom_col=None, start_col=None, end_col=None)[source]¶: Return a chrom, start, stop tuple for viewing a file.

ucsc_links(dataset, type, app, base_url)[source]¶

sniff_prefix(file_prefix)[source]¶

Determines whether the file is in customtrack format.

CustomTrack files are built within Galaxy and are basically bed or interval files with the first line looking something like this.

track name=”User Track” description=”User Supplied Track (from Galaxy)” color=0,0,0 visibility=1

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname( 'complete.bed' )
>>> CustomTrack().sniff( fname )
False
>>> fname = get_test_fname( 'ucsc.customtrack' )
>>> CustomTrack().sniff( fname )
True

metadata_spec = {'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.interval.ENCODEPeak(**kwd)[source]¶

Bases: galaxy.datatypes.interval.Interval

Human ENCODE peak format. There are both broad and narrow peak formats. Formats are very similar; narrow peak has an additional column, though.

Broad peak ( http://genome.ucsc.edu/FAQ/FAQformat#format13 ): This format is used to provide called regions of signal enrichment based on pooled, normalized (interpreted) data. It is a BED 6+3 format.

Narrow peak http://genome.ucsc.edu/FAQ/FAQformat#format12 and : This format is used to provide called peaks of signal enrichment based on pooled, normalized (interpreted) data. It is a BED6+4 format.

edam_format = 'format_3612'¶

file_ext = 'encodepeak'¶

column_names = ['Chrom', 'Start', 'End', 'Name', 'Score', 'Strand', 'SignalValue', 'pValue', 'qValue', 'Peak']¶

data_sources: Dict[str, str] = {'data': 'tabix', 'index': 'bigwig'}¶: Add metadata elements

sniff(filename)[source]¶

metadata_spec = {'chromCol': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'endCol': <galaxy.model.metadata.MetadataElementSpec object>, 'nameCol': <galaxy.model.metadata.MetadataElementSpec object>, 'startCol': <galaxy.model.metadata.MetadataElementSpec object>, 'strandCol': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.interval.ChromatinInteractions(**kwd)[source]¶

Bases: galaxy.datatypes.interval.Interval

Chromatin interactions obtained from 3C/5C/Hi-C experiments.

file_ext = 'chrint'¶

track_type: Optional[str] = 'DiagonalHeatmapTrack'¶

data_sources: Dict[str, str] = {'data': 'tabix', 'index': 'bigwig'}¶

column_names = ['Chrom1', 'Start1', 'End1', 'Chrom2', 'Start2', 'End2', 'Value']¶: Add metadata elements

metadata_spec = {'chrom1Col': <galaxy.model.metadata.MetadataElementSpec object>, 'chrom2Col': <galaxy.model.metadata.MetadataElementSpec object>, 'chromCol': <galaxy.model.metadata.MetadataElementSpec object>, 'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>, 'end1Col': <galaxy.model.metadata.MetadataElementSpec object>, 'end2Col': <galaxy.model.metadata.MetadataElementSpec object>, 'endCol': <galaxy.model.metadata.MetadataElementSpec object>, 'nameCol': <galaxy.model.metadata.MetadataElementSpec object>, 'start1Col': <galaxy.model.metadata.MetadataElementSpec object>, 'start2Col': <galaxy.model.metadata.MetadataElementSpec object>, 'startCol': <galaxy.model.metadata.MetadataElementSpec object>, 'strandCol': <galaxy.model.metadata.MetadataElementSpec object>, 'valueCol': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)[source]¶

class galaxy.datatypes.interval.ScIdx(**kwd)[source]¶

Bases: galaxy.datatypes.tabular.Tabular

ScIdx files are 1-based and consist of strand-specific coordinate counts. They always have 5 columns, and the first row is the column labels: ‘chrom’, ‘index’, ‘forward’, ‘reverse’, ‘value’. Each line following the first consists of data: chromosome name (type str), peak index (type int), Forward strand peak count (type int), Reverse strand peak count (type int) and value (type int). The value of the 5th ‘value’ column is the sum of the forward and reverse peak count values.

metadata_spec = {'column_names': <galaxy.model.metadata.MetadataElementSpec object>, 'column_types': <galaxy.model.metadata.MetadataElementSpec object>, 'columns': <galaxy.model.metadata.MetadataElementSpec object>, 'comment_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'delimiter': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

file_ext = 'scidx'¶

__init__(**kwd)[source]¶: Initialize scidx datatype.

sniff_prefix(file_prefix)[source]¶: Checks for ‘scidx-ness.’

galaxy.datatypes.isa module¶

ISA datatype

See https://github.com/ISA-tools

galaxy.datatypes.isa.utf8_text_file_open(path)[source]¶

class galaxy.datatypes.isa.IsaTab(**kwd)[source]¶

Bases: galaxy.datatypes.isa._Isa

file_ext = 'isa-tab'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.isa.IsaJson(**kwd)[source]¶

Bases: galaxy.datatypes.isa._Isa

file_ext = 'isa-json'¶

__init__(**kwd)[source]¶: Initialize the datatype

metadata_spec = {'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.media module¶

Video classes

galaxy.datatypes.media.ffprobe(path)[source]¶

class galaxy.datatypes.media.Audio(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

set_meta(dataset, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

metadata_spec = {'audio_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'audio_streams': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'duration': <galaxy.model.metadata.MetadataElementSpec object>, 'sample_rates': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.media.Video(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

set_meta(dataset, **kwd)[source]¶: Unimplemented method, allows guessing of metadata from contents of file

metadata_spec = {'audio_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'audio_streams': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fps': <galaxy.model.metadata.MetadataElementSpec object>, 'resolution_h': <galaxy.model.metadata.MetadataElementSpec object>, 'resolution_w': <galaxy.model.metadata.MetadataElementSpec object>, 'video_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'video_streams': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.media.Mkv(**kwd)[source]¶

Bases: galaxy.datatypes.media.Video

file_ext = 'mkv'¶

sniff(filename)[source]¶

metadata_spec = {'audio_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'audio_streams': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fps': <galaxy.model.metadata.MetadataElementSpec object>, 'resolution_h': <galaxy.model.metadata.MetadataElementSpec object>, 'resolution_w': <galaxy.model.metadata.MetadataElementSpec object>, 'video_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'video_streams': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.media.Mp4(**kwd)[source]¶

Bases: galaxy.datatypes.media.Video

Class that reads MP4 video file. >>> from galaxy.datatypes.sniff import sniff_with_cls >>> sniff_with_cls(Mp4, ‘video_1.mp4’) True >>> sniff_with_cls(Mp4, ‘audio_1.mp4’) False

file_ext = 'mp4'¶

sniff(filename)[source]¶

metadata_spec = {'audio_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'audio_streams': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fps': <galaxy.model.metadata.MetadataElementSpec object>, 'resolution_h': <galaxy.model.metadata.MetadataElementSpec object>, 'resolution_w': <galaxy.model.metadata.MetadataElementSpec object>, 'video_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'video_streams': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.media.Flv(**kwd)[source]¶

Bases: galaxy.datatypes.media.Video

file_ext = 'flv'¶

sniff(filename)[source]¶

metadata_spec = {'audio_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'audio_streams': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fps': <galaxy.model.metadata.MetadataElementSpec object>, 'resolution_h': <galaxy.model.metadata.MetadataElementSpec object>, 'resolution_w': <galaxy.model.metadata.MetadataElementSpec object>, 'video_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'video_streams': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.media.Mpg(**kwd)[source]¶

Bases: galaxy.datatypes.media.Video

file_ext = 'mpg'¶

sniff(filename)[source]¶

metadata_spec = {'audio_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'audio_streams': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'fps': <galaxy.model.metadata.MetadataElementSpec object>, 'resolution_h': <galaxy.model.metadata.MetadataElementSpec object>, 'resolution_w': <galaxy.model.metadata.MetadataElementSpec object>, 'video_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'video_streams': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.media.Mp3(**kwd)[source]¶

Bases: galaxy.datatypes.media.Audio

Class that reads MP3 audio file. >>> from galaxy.datatypes.sniff import sniff_with_cls >>> sniff_with_cls(Mp3, ‘audio_2.mp3’) True >>> sniff_with_cls(Mp3, ‘audio_1.wav’) False

file_ext = 'mp3'¶

sniff(filename)[source]¶

metadata_spec = {'audio_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'audio_streams': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'duration': <galaxy.model.metadata.MetadataElementSpec object>, 'sample_rates': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.media.Wav(**kwd)[source]¶

Bases: galaxy.datatypes.media.Audio

Class that reads WAV audio file >>> from galaxy.datatypes.sniff import sniff_with_cls >>> sniff_with_cls(Wav, ‘hello.wav’) True >>> sniff_with_cls(Wav, ‘audio_2.mp3’) False >>> sniff_with_cls(Wav, ‘drugbank_drugs.cml’) False

file_ext = 'wav'¶

blurb = 'RIFF WAV Audio file'¶

is_binary = True¶

get_mime()[source]¶: Returns the mime type of the datatype.

sniff(filename)[source]¶

set_meta(dataset, overwrite=True, **kwd)[source]¶: Set the metadata for this dataset from the file contents.

metadata_spec = {'audio_codecs': <galaxy.model.metadata.MetadataElementSpec object>, 'audio_streams': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'duration': <galaxy.model.metadata.MetadataElementSpec object>, 'nchannels': <galaxy.model.metadata.MetadataElementSpec object>, 'nframes': <galaxy.model.metadata.MetadataElementSpec object>, 'rate': <galaxy.model.metadata.MetadataElementSpec object>, 'sample_rates': <galaxy.model.metadata.MetadataElementSpec object>, 'sampwidth': <galaxy.model.metadata.MetadataElementSpec object>}¶

galaxy.datatypes.metadata module¶

Expose the model metadata module as a datatype module also, allowing it to live in galaxy.model means the model module doesn’t have any dependencies on th datatypes module. This module will need to remain here for datatypes living in the tool shed so we might as well keep and use this interface from the datatypes module.

class galaxy.datatypes.metadata.Statement(target)[source]¶

Bases: object

This class inserts its target into a list in the surrounding class. the data.Data class has a metaclass which executes these statements. This is how we shove the metadata element spec into the class.

__init__(target)[source]¶: Initialize self. See help(type(self)) for accurate signature.

classmethod process(element)[source]¶

class galaxy.datatypes.metadata.MetadataCollection(parent)[source]¶

Bases: collections.abc.Mapping

MetadataCollection is not a collection at all, but rather a proxy to the real metadata which is stored as a Dictionary. This class handles processing the metadata elements when they are set and retrieved, returning default values in cases when metadata is not set.

__init__(parent)[source]¶: Initialize self. See help(type(self)) for accurate signature.

get_parent()[source]¶

set_parent(parent)[source]¶

property parent¶

property spec¶

remove_key(name)[source]¶

element_is_set(name)[source]¶

check if the meta data with the given name is set, i.e.

if the such a metadata actually exists and
if its value differs from no_value

Parameters: name – the name of the metadata element
Returns: True if the value differes from the no_value False if its equal of if no metadata with the name is specified

get_metadata_parameter(name, **kwd)[source]¶

make_dict_copy(to_copy)[source]¶: Makes a deep copy of input iterable to_copy according to self.spec

property requires_dataset_id¶

from_JSON_dict(filename=None, path_rewriter=None, json_dict=None)[source]¶

to_JSON_dict(filename=None)[source]¶

class galaxy.datatypes.metadata.MetadataSpecCollection(*args, **kwds)[source]¶

Bases: collections.OrderedDict

A simple extension of OrderedDict which allows cleaner access to items and allows the values to be iterated over directly as if it were a list. append() is also implemented for simplicity and does not “append”.

__init__(*args, **kwds)[source]¶: Initialize self. See help(type(self)) for accurate signature.

append(item)[source]¶

class galaxy.datatypes.metadata.MetadataParameter(spec)[source]¶

Bases: object

__init__(spec)[source]¶: Initialize self. See help(type(self)) for accurate signature.

get_field(value=None, context=None, other_values=None, **kwd)[source]¶

to_string(value)[source]¶

to_safe_string(value)[source]¶

make_copy(value, target_context=None, source_context=None)[source]¶

classmethod marshal(value)[source]¶: This method should/can be overridden to convert the incoming value to whatever type it is supposed to be.

validate(value)[source]¶: Throw an exception if the value is invalid.

unwrap(form_value)[source]¶: Turns a value into its storable form.

wrap(value, session)[source]¶: Turns a value into its usable form.

from_external_value(value, parent)[source]¶: Turns a value read from an external dict into its value to be pushed directly into the metadata dict.

to_external_value(value)[source]¶: Turns a value read from a metadata into its value to be pushed directly into the external dict.

class galaxy.datatypes.metadata.MetadataElementSpec(datatype, name=None, desc=None, param=<class 'galaxy.model.metadata.MetadataParameter'>, default=None, no_value=None, visible=True, set_in_upload=False, **kwargs)[source]¶

Bases: object

Defines a metadata element and adds it to the metadata_spec (which is a MetadataSpecCollection) of datatype.

__init__(datatype, name=None, desc=None, param=<class 'galaxy.model.metadata.MetadataParameter'>, default=None, no_value=None, visible=True, set_in_upload=False, **kwargs)[source]¶: Initialize self. See help(type(self)) for accurate signature.

get(name, default=None)[source]¶

wrap(value, session)[source]¶: Turns a stored value into its usable form.

unwrap(value)[source]¶: Turns an incoming value into its storable form.

class galaxy.datatypes.metadata.SelectParameter(spec)[source]¶

Bases: galaxy.model.metadata.MetadataParameter

__init__(spec)[source]¶: Initialize self. See help(type(self)) for accurate signature.

to_string(value)[source]¶

get_field(value=None, context=None, other_values=None, values=None, **kwd)[source]¶

wrap(value, session)[source]¶: Turns a value into its usable form.

classmethod marshal(value)[source]¶: This method should/can be overridden to convert the incoming value to whatever type it is supposed to be.

class galaxy.datatypes.metadata.DBKeyParameter(spec)[source]¶

Bases: galaxy.model.metadata.SelectParameter

get_field(value=None, context=None, other_values=None, values=None, **kwd)[source]¶

class galaxy.datatypes.metadata.RangeParameter(spec)[source]¶

Bases: galaxy.model.metadata.SelectParameter

__init__(spec)[source]¶: Initialize self. See help(type(self)) for accurate signature.

get_field(value=None, context=None, other_values=None, values=None, **kwd)[source]¶

classmethod marshal(value)[source]¶: This method should/can be overridden to convert the incoming value to whatever type it is supposed to be.

class galaxy.datatypes.metadata.ColumnParameter(spec)[source]¶

Bases: galaxy.model.metadata.RangeParameter

get_field(value=None, context=None, other_values=None, values=None, **kwd)[source]¶

class galaxy.datatypes.metadata.ColumnTypesParameter(spec)[source]¶

Bases: galaxy.model.metadata.MetadataParameter

to_string(value)[source]¶

class galaxy.datatypes.metadata.ListParameter(spec)[source]¶

Bases: galaxy.model.metadata.MetadataParameter

to_string(value)[source]¶

class galaxy.datatypes.metadata.DictParameter(spec)[source]¶

Bases: galaxy.model.metadata.MetadataParameter

to_string(value)[source]¶

to_safe_string(value)[source]¶

class galaxy.datatypes.metadata.PythonObjectParameter(spec)[source]¶

Bases: galaxy.model.metadata.MetadataParameter

to_string(value)[source]¶

get_field(value=None, context=None, other_values=None, **kwd)[source]¶

classmethod marshal(value)[source]¶: This method should/can be overridden to convert the incoming value to whatever type it is supposed to be.

class galaxy.datatypes.metadata.FileParameter(spec)[source]¶

Bases: galaxy.model.metadata.MetadataParameter

to_string(value)[source]¶

to_safe_string(value)[source]¶

get_field(value=None, context=None, other_values=None, **kwd)[source]¶

wrap(value, session)[source]¶: Turns a value into its usable form.

make_copy(value, target_context, source_context)[source]¶

classmethod marshal(value)[source]¶: This method should/can be overridden to convert the incoming value to whatever type it is supposed to be.

from_external_value(value, parent, path_rewriter=None)[source]¶: Turns a value read from a external dict into its value to be pushed directly into the metadata dict.

to_external_value(value)[source]¶: Turns a value read from a metadata into its value to be pushed directly into the external dict.

new_file(dataset=None, **kwds)[source]¶

class galaxy.datatypes.metadata.MetadataTempFile(**kwds)[source]¶

Bases: object

tmp_dir = 'database/tmp'¶

__init__(**kwds)[source]¶: Initialize self. See help(type(self)) for accurate signature.

property file_name¶

to_JSON()[source]¶

classmethod from_JSON(json_dict)[source]¶

classmethod is_JSONified_value(value)[source]¶

classmethod cleanup_from_JSON_dict_filename(filename)[source]¶

galaxy.datatypes.microarrays module¶

class galaxy.datatypes.microarrays.GenericMicroarrayFile(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

Abstract class for most of the microarray files.

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek. This method is used by various subclasses of Text.

get_mime()[source]¶: Returns the mime type of the datatype

metadata_spec = {'block_count': <galaxy.model.metadata.MetadataElementSpec object>, 'block_type': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'file_format': <galaxy.model.metadata.MetadataElementSpec object>, 'file_type': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_data_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_optional_header_records': <galaxy.model.metadata.MetadataElementSpec object>, 'version_number': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.microarrays.Gal(**kwd)[source]¶

Bases: galaxy.datatypes.microarrays.GenericMicroarrayFile

Gal File format described at: http://mdc.custhelp.com/app/answers/detail/a_id/18883/#gal

edam_format = 'format_3829'¶

edam_data = 'data_3110'¶

file_ext = 'gal'¶

sniff_prefix(file_prefix)[source]¶: Try to guess if the file is a Gal file. >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘test.gal’) >>> Gal().sniff(fname) True >>> fname = get_test_fname(‘test.gpr’) >>> Gal().sniff(fname) False

set_meta(dataset, **kwd)[source]¶: Set metadata for Gal file.

metadata_spec = {'block_count': <galaxy.model.metadata.MetadataElementSpec object>, 'block_type': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'file_format': <galaxy.model.metadata.MetadataElementSpec object>, 'file_type': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_data_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_optional_header_records': <galaxy.model.metadata.MetadataElementSpec object>, 'version_number': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.microarrays.Gpr(**kwd)[source]¶

Bases: galaxy.datatypes.microarrays.GenericMicroarrayFile

Gpr File format described at: http://mdc.custhelp.com/app/answers/detail/a_id/18883/#gpr

edam_format = 'format_3829'¶

edam_data = 'data_3110'¶

file_ext = 'gpr'¶

sniff_prefix(file_prefix)[source]¶: Try to guess if the file is a Gpr file. >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘test.gpr’) >>> Gpr().sniff(fname) True >>> fname = get_test_fname(‘test.gal’) >>> Gpr().sniff(fname) False

set_meta(dataset, **kwd)[source]¶: Set metadata for Gpr file.

metadata_spec = {'block_count': <galaxy.model.metadata.MetadataElementSpec object>, 'block_type': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'file_format': <galaxy.model.metadata.MetadataElementSpec object>, 'file_type': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_data_columns': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_optional_header_records': <galaxy.model.metadata.MetadataElementSpec object>, 'version_number': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

galaxy.datatypes.molecules module¶

galaxy.datatypes.molecules.count_lines(filename, non_empty=False)[source]¶: counting the number of lines from the ‘filename’ file

class galaxy.datatypes.molecules.GenericMolFile(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

Abstract class for most of the molecule files.

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek. This method is used by various subclasses of Text.

get_mime()[source]¶: Returns the mime type of the datatype

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_molecules': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.molecules.MOL(**kwd)[source]¶

Bases: galaxy.datatypes.molecules.GenericMolFile

file_ext = 'mol'¶

set_meta(dataset, **kwd)[source]¶: Set the number molecules, in the case of MOL its always one.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_molecules': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.molecules.SDF(**kwd)[source]¶

Bases: galaxy.datatypes.molecules.GenericMolFile

file_ext = 'sdf'¶

sniff_prefix(file_prefix)[source]¶

Try to guess if the file is a SDF2 file.

An SDfile (structure-data file) can contain multiple compounds.

Each compound starts with a block in V2000 or V3000 molfile format, which ends with a line equal to ‘M END’. This is followed by a non-structural data block, which ends with a line equal to ‘$$$$’.

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('drugbank_drugs.sdf')
>>> SDF().sniff(fname)
True
>>> fname = get_test_fname('github88.v3k.sdf')
>>> SDF().sniff(fname)
True
>>> fname = get_test_fname('chebi_57262.v3k.mol')
>>> SDF().sniff(fname)
False

set_meta(dataset, **kwd)[source]¶: Set the number of molecules in dataset.

classmethod split(input_datasets, subdir_generator_function, split_params)[source]¶: Split the input files by molecule records.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_molecules': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.molecules.MOL2(**kwd)[source]¶

Bases: galaxy.datatypes.molecules.GenericMolFile

file_ext = 'mol2'¶

sniff_prefix(file_prefix)[source]¶

Try to guess if the file is a MOL2 file.

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('drugbank_drugs.mol2')
>>> MOL2().sniff(fname)
True
>>> fname = get_test_fname('drugbank_drugs.cml')
>>> MOL2().sniff(fname)
False

set_meta(dataset, **kwd)[source]¶: Set the number of lines of data in dataset.

classmethod split(input_datasets, subdir_generator_function, split_params)[source]¶: Split the input files by molecule records.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_molecules': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.molecules.FPS(**kwd)[source]¶

Bases: galaxy.datatypes.molecules.GenericMolFile

chemfp fingerprint file: http://code.google.com/p/chem-fingerprints/wiki/FPS

file_ext = 'fps'¶

sniff_prefix(file_prefix)[source]¶

Try to guess if the file is a FPS file.

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('q.fps')
>>> FPS().sniff(fname)
True
>>> fname = get_test_fname('drugbank_drugs.cml')
>>> FPS().sniff(fname)
False

set_meta(dataset, **kwd)[source]¶: Set the number of lines of data in dataset.

classmethod split(input_datasets, subdir_generator_function, split_params)[source]¶: Split the input files by fingerprint records.

static merge(split_files, output_file)[source]¶: Merging fps files requires merging the header manually. We take the header from the first file.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_molecules': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.molecules.OBFS(**kwd)[source]¶

Bases: galaxy.datatypes.binary.Binary

OpenBabel Fastsearch format (fs).

file_ext = 'obfs'¶

composite_type: Optional[str] = 'basic'¶

__init__(**kwd)[source]¶: A Fastsearch Index consists of a binary file with the fingerprints and a pointer the actual molecule file.

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek and blurb text.

display_peek(dataset)[source]¶: Create HTML content, used for displaying peek.

get_mime()[source]¶: Returns the mime type of the datatype (pretend it is text for peek)

merge(output_file, extra_merge_args)[source]¶: Merging Fastsearch indices is not supported.

split(input_datasets, subdir_generator_function, split_params)[source]¶: Splitting Fastsearch indices is not supported.

metadata_spec = {'base_name': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.molecules.DRF(**kwd)[source]¶

Bases: galaxy.datatypes.molecules.GenericMolFile

file_ext = 'drf'¶

set_meta(dataset, **kwd)[source]¶: Set the number of lines of data in dataset.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_molecules': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.molecules.PHAR(**kwd)[source]¶

Bases: galaxy.datatypes.molecules.GenericMolFile

Pharmacophore database format from silicos-it.

file_ext = 'phar'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek. This method is used by various subclasses of Text.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_molecules': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.molecules.PDB(**kwd)[source]¶

Bases: galaxy.datatypes.molecules.GenericMolFile

Protein Databank format. http://www.wwpdb.org/documentation/format33/v3.3.html

file_ext = 'pdb'¶

sniff_prefix(file_prefix)[source]¶

Try to guess if the file is a PDB file.

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('5e5z.pdb')
>>> PDB().sniff(fname)
True
>>> fname = get_test_fname('drugbank_drugs.cml')
>>> PDB().sniff(fname)
False

set_meta(dataset, **kwd)[source]¶: Find Chain_IDs for metadata.

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek. This method is used by various subclasses of Text.

metadata_spec = {'chain_ids': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_molecules': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.molecules.PDBQT(**kwd)[source]¶

Bases: galaxy.datatypes.molecules.GenericMolFile

PDBQT Autodock and Autodock Vina format http://autodock.scripps.edu/faqs-help/faq/what-is-the-format-of-a-pdbqt-file

file_ext = 'pdbqt'¶

sniff_prefix(file_prefix)[source]¶

Try to guess if the file is a PDBQT file.

>>> from galaxy.datatypes.sniff import get_test_fname
>>> fname = get_test_fname('NuBBE_1_obabel_3D.pdbqt')
>>> PDBQT().sniff(fname)
True
>>> fname = get_test_fname('drugbank_drugs.cml')
>>> PDBQT().sniff(fname)
False

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek. This method is used by various subclasses of Text.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_molecules': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.molecules.PQR(**kwd)[source]¶

Bases: galaxy.datatypes.molecules.GenericMolFile

Protein Databank format. https://apbs-pdb2pqr.readthedocs.io/en/latest/formats/pqr.html

file_ext = 'pqr'¶

get_matcher()[source]¶

Atom and HETATM line fields are space separated, match group:

0: Field_name: A string which specifies the type of PQR entry: ATOM or HETATM.
1: Atom_number: An integer which provides the atom index.
2: Atom_name: A string which provides the atom name.
3: Residue_name: A string which provides the residue name.
5: Chain_ID (Optional, group 4 is whole field): An optional string which provides the chain ID of the atom. Note that chain ID support is a new feature of APBS 0.5.0 and later versions.
6: Residue_number: An integer which provides the residue index.
7: X 8: Y 9: Z: 3 floats which provide the atomic coordinates (in angstroms)
10: Charge: A float which provides the atomic charge (in electrons).
11: Radius: A float which provides the atomic radius (in angstroms).

sniff_prefix(file_prefix)[source]¶: Try to guess if the file is a PQR file. >>> from galaxy.datatypes.sniff import get_test_fname >>> fname = get_test_fname(‘5e5z.pqr’) >>> PQR().sniff(fname) True >>> fname = get_test_fname(‘drugbank_drugs.cml’) >>> PQR().sniff(fname) False

set_meta(dataset, **kwd)[source]¶: Find Optional Chain_IDs for metadata.

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek. This method is used by various subclasses of Text.

metadata_spec = {'chain_ids': <galaxy.model.metadata.MetadataElementSpec object>, 'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>, 'number_of_molecules': <galaxy.model.metadata.MetadataElementSpec object>}¶

sniff(filename)¶

class galaxy.datatypes.molecules.grd(**kwd)[source]¶

Bases: galaxy.datatypes.data.Text

file_ext = 'grd'¶

set_peek(dataset, is_multi_byte=False)[source]¶: Set the peek. This method is used by various subclasses of Text.

metadata_spec = {'data_lines': <galaxy.model.metadata.MetadataElementSpec object>, 'dbkey': <galaxy.model.metadata.MetadataElementSpec object>}¶

class galaxy.datatypes.molecules.grdtgz(**kwd)[source]¶: Bases: galaxy.datatypes.binary.Binary