Exemplo n.º 1
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 def set_sam_tag(cls, count_tag, bamfile_name, tag_regex):
     """Add key:value pair to class variable: has_sam_tag.
     
     Keyword Arguments:
     count_tag -- boolean on whether to count with this tag
     bamfile_name -- file to query for tag
     tag_regex -- regular expression for the tag (eg 'NA:i:(\d+)')
     """
     (run_pipe_worked, sam_sample) = run_pipe(['samtools view {}'.format(bamfile_name), 'head -n 10'])
     if run_pipe_worked:
         return cls.process_set_sam_tag(sam_sample, count_tag, tag_regex)
     else:
         raise MetageneError("Checking the bam file failed with error: {}".format(sam_sample))
Exemplo n.º 2
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 def set_chromosome_sizes(cls, bamfile):
     """Set chromosome_sizes dictionary with BAM header.
     
     Keyword Arguments:
     bamfile -- name of bamfile
     """
     (run_pipe_worked, header) = run_pipe(["samtools view -H {}".format(bamfile)])
     if not run_pipe_worked:
         raise MetageneError("Could not open BAM file {}".format(bamfile))
     else:
         try:
             return cls.extract_chromosome_sizes(header)
         except MetageneError as err:
             raise MetageneError("Error processing {} header\n{}".format(bamfile, err.message))
Exemplo n.º 3
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 def set_chromosome_sizes(cls, bamfile):
     """Set chromosome_sizes dictionary with BAM header.
     
     Keyword Arguments:
     bamfile -- name of bamfile
     """
     (run_pipe_worked,
      header) = run_pipe(["samtools view -H {}".format(bamfile)])
     if not run_pipe_worked:
         raise MetageneError("Could not open BAM file {}".format(bamfile))
     else:
         try:
             return cls.extract_chromosome_sizes(header)
         except MetageneError as err:
             raise MetageneError("Error processing {} header\n{}".format(
                 bamfile, err.message))
Exemplo n.º 4
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 def set_sam_tag(cls, count_tag, bamfile_name, tag_regex):
     """Add key:value pair to class variable: has_sam_tag.
     
     Keyword Arguments:
     count_tag -- boolean on whether to count with this tag
     bamfile_name -- file to query for tag
     tag_regex -- regular expression for the tag (eg 'NA:i:(\d+)')
     """
     (run_pipe_worked, sam_sample) = run_pipe(
         ['samtools view {}'.format(bamfile_name), 'head -n 10'])
     if run_pipe_worked:
         return cls.process_set_sam_tag(sam_sample, count_tag, tag_regex)
     else:
         raise MetageneError(
             "Checking the bam file failed with error: {}".format(
                 sam_sample))
def metagene_count():
    """Chain of command for metagene_count analysis."""
    arguments = get_arguments()
    # confirm BAM file and extract chromosome sizes
    Read.set_chromosome_sizes(arguments.alignment)
    ##TODO: create a list of chromosomes to analyze and/or exclude
    # create chromosome conversion dictionary for feature (GFF/BED) to alignment (BAM)
    Feature.set_chromosome_conversion(arguments.chromosome_names, Read.chromosome_sizes.keys())

    # define has_abundance and has_mappings tags for Read class
    Read.set_sam_tag(arguments.extract_abundance, arguments.alignment, "NA:i:(\d+)")
    Read.set_sam_tag(arguments.extract_mappings, arguments.alignment, "NH:i:(\d+)")

    # define the metagene array shape (left padding, start, internal, end, right padding)
    # metagene = padding ---- internal region ---- padding 
    try:
        metagene = Metagene(arguments.interval_size, arguments.padding, arguments.padding)
        print "Metagene definition:\t{}".format(metagene)
    except MetageneError as err:
        print err
        raise MetageneError("Unable to create the metagene template")

    try:
        Feature.set_format(arguments.feature)  # assign file format for the feature file
        print "Reading feature file as {} format".format(Feature.format)
    except MetageneError as err:
        print err
        raise MetageneError("Unable to create the feature object")

    # print out the header line...
    if not arguments.interval_variable:
        with open("{}.metagene_counts.csv".format(arguments.output_prefix), 'w') as output_file:
            output_file.write("# Metagene:\t{}\n".format(metagene))  # define for plotting later
            output_file.write(metagene.print_full())

    # for each feature
    with open(arguments.feature, 'r') as feature_file:
        for feature_line in read_chunk(feature_file, 1024):
            if feature_line[0] != "#":  # skip comment lines
                # change creation with feature_method
                feature = Feature.create(arguments.feature_count, metagene, feature_line, arguments.count_splicing,
                                         arguments.ignore_strand)

                # pull out sam file lines; it is important to use Feature.get_samtools_region(chromosome_lengths) rather
                # than Feature.get_chromosome_region() because only the first ensures that the interval does not
                # extend beyond the length of the chromosome which makes samtools view return no reads
                (run_pipe_worked, sam_sample) = run_pipe(['samtools view {} {}'.format(
                    arguments.alignment,
                    feature.get_samtools_region())])
                if run_pipe_worked:
                    for samline in sam_sample:
                        if len(samline) > 0:
                            # create Read feature
                            (created_read, read) = Read.create_from_sam(samline,
                                                                        Feature.chromosome_conversion.values(),
                                                                        arguments.count_method,
                                                                        arguments.uniquely_mapping,
                                                                        arguments.ignore_strand,
                                                                        arguments.count_secondary_alignments,
                                                                        arguments.count_failed_quality_control,
                                                                        arguments.count_PCR_optical_duplicate,
                                                                        arguments.count_supplementary_alignment)

                            # count read (if it exists)
                            if created_read:
                                feature.count_read(read, arguments.count_method, arguments.count_splicing,
                                                   arguments.count_partial_reads, arguments.ignore_strand)

                    # output the resulting metagene
                    with open("{}.metagene_counts.csv".format(arguments.output_prefix), 'a') as output_file:
                        output_file.write(
                            "{}\n".format(feature.print_metagene(interval_override=arguments.interval_variable)))

                else:
                    raise MetageneError("Could not pull chromosomal region {} for feature {} from BAM file {}.".format(
                        feature.get_chromosome_region(),
                        feature.name,
                        arguments.alignment))
Exemplo n.º 6
0
def metagene_count():
    """Chain of command for metagene_count analysis."""
    arguments = get_arguments()
    # confirm BAM file and extract chromosome sizes
    Read.set_chromosome_sizes(arguments.alignment)
    ##TODO: create a list of chromosomes to analyze and/or exclude
    # create chromosome conversion dictionary for feature (GFF/BED) to alignment (BAM)
    Feature.set_chromosome_conversion(arguments.chromosome_names,
                                      Read.chromosome_sizes.keys())

    # define has_abundance and has_mappings tags for Read class
    Read.set_sam_tag(arguments.extract_abundance, arguments.alignment,
                     "NA:i:(\d+)")
    Read.set_sam_tag(arguments.extract_mappings, arguments.alignment,
                     "NH:i:(\d+)")

    # define the metagene array shape (left padding, start, internal, end, right padding)
    # metagene = padding ---- internal region ---- padding
    try:
        metagene = Metagene(arguments.interval_size, arguments.padding,
                            arguments.padding)
        print "Metagene definition:\t{}".format(metagene)
    except MetageneError as err:
        print err
        raise MetageneError("Unable to create the metagene template")

    try:
        Feature.set_format(
            arguments.feature)  # assign file format for the feature file
        print "Reading feature file as {} format".format(Feature.format)
    except MetageneError as err:
        print err
        raise MetageneError("Unable to create the feature object")

    # print out the header line...
    if not arguments.interval_variable:
        with open("{}.metagene_counts.csv".format(arguments.output_prefix),
                  'w') as output_file:
            output_file.write("# Metagene:\t{}\n".format(
                metagene))  # define for plotting later
            output_file.write(metagene.print_full())

    # for each feature
    with open(arguments.feature, 'r') as feature_file:
        for feature_line in read_chunk(feature_file, 1024):
            if feature_line[0] != "#":  # skip comment lines
                # change creation with feature_method
                feature = Feature.create(arguments.feature_count, metagene,
                                         feature_line,
                                         arguments.count_splicing,
                                         arguments.ignore_strand)

                # pull out sam file lines; it is important to use Feature.get_samtools_region(chromosome_lengths) rather
                # than Feature.get_chromosome_region() because only the first ensures that the interval does not
                # extend beyond the length of the chromosome which makes samtools view return no reads
                (run_pipe_worked, sam_sample) = run_pipe([
                    'samtools view {} {}'.format(arguments.alignment,
                                                 feature.get_samtools_region())
                ])
                if run_pipe_worked:
                    for samline in sam_sample:
                        if len(samline) > 0:
                            # create Read feature
                            (created_read, read) = Read.create_from_sam(
                                samline,
                                Feature.chromosome_conversion.values(),
                                arguments.count_method,
                                arguments.uniquely_mapping,
                                arguments.ignore_strand,
                                arguments.count_secondary_alignments,
                                arguments.count_failed_quality_control,
                                arguments.count_PCR_optical_duplicate,
                                arguments.count_supplementary_alignment)

                            # count read (if it exists)
                            if created_read:
                                feature.count_read(
                                    read, arguments.count_method,
                                    arguments.count_splicing,
                                    arguments.count_partial_reads,
                                    arguments.ignore_strand)

                    # output the resulting metagene
                    with open(
                            "{}.metagene_counts.csv".format(
                                arguments.output_prefix), 'a') as output_file:
                        output_file.write("{}\n".format(
                            feature.print_metagene(interval_override=arguments.
                                                   interval_variable)))

                else:
                    raise MetageneError(
                        "Could not pull chromosomal region {} for feature {} from BAM file {}."
                        .format(feature.get_chromosome_region(), feature.name,
                                arguments.alignment))