Ejemplo n.º 1
0
def _goleft_indexcov(bam_file, data, out_dir):
    """Use goleft indexcov to estimate coverage distributions using BAM index.

    Only used for whole genome runs as captures typically don't have enough data
    to be useful for index-only summaries.
    """
    if not dd.get_coverage_interval(data) == "genome":
        return []
    out_dir = utils.safe_makedir(os.path.join(out_dir, "indexcov"))
    out_files = [os.path.join(out_dir, "%s-indexcov.%s" % (dd.get_sample_name(data), ext))
                 for ext in ["roc", "ped", "bed.gz"]]
    if not utils.file_uptodate(out_files[-1], bam_file):
        with transaction.tx_tmpdir(data) as tmp_dir:
            tmp_dir = utils.safe_makedir(os.path.join(tmp_dir, dd.get_sample_name(data)))
            gender_chroms = [x.name for x in ref.file_contigs(dd.get_ref_file(data)) if chromhacks.is_sex(x.name)]
            gender_args = "--sex %s" % (",".join(gender_chroms)) if gender_chroms else ""
            cmd = "goleft indexcov --directory {tmp_dir} {gender_args} -- {bam_file}"
            try:
                do.run(cmd.format(**locals()), "QC: goleft indexcov")
            except subprocess.CalledProcessError as msg:
                if not ("indexcov: no usable" in str(msg) or
                        ("indexcov: expected" in str(msg) and "sex chromosomes, found:" in str(msg))):
                    raise
            for out_file in out_files:
                orig_file = os.path.join(tmp_dir, os.path.basename(out_file))
                if utils.file_exists(orig_file):
                    utils.copy_plus(orig_file, out_file)
    # MultiQC needs non-gzipped/BED inputs so unpack the file
    out_bed = out_files[-1].replace(".bed.gz", ".tsv")
    if utils.file_exists(out_files[-1]) and not utils.file_exists(out_bed):
        with transaction.file_transaction(data, out_bed) as tx_out_bed:
            cmd = "gunzip -c %s > %s" % (out_files[-1], tx_out_bed)
            do.run(cmd, "Unpack indexcov BED file")
    out_files[-1] = out_bed
    return [x for x in out_files if utils.file_exists(x)]
Ejemplo n.º 2
0
def _goleft_indexcov(bam_file, data, out_dir):
    """Use goleft indexcov to estimate coverage distributions using BAM index.

    Only used for whole genome runs as captures typically don't have enough data
    to be useful for index-only summaries.
    """
    if not dd.get_coverage_interval(data) == "genome":
        return []
    out_dir = utils.safe_makedir(os.path.join(out_dir, "indexcov"))
    out_files = [os.path.join(out_dir, "%s-indexcov.%s" % (dd.get_sample_name(data), ext))
                 for ext in ["roc", "ped", "bed.gz"]]
    if not utils.file_uptodate(out_files[-1], bam_file):
        with transaction.tx_tmpdir(data) as tmp_dir:
            tmp_dir = utils.safe_makedir(os.path.join(tmp_dir, dd.get_sample_name(data)))
            gender_chroms = [x.name for x in ref.file_contigs(dd.get_ref_file(data)) if chromhacks.is_sex(x.name)]
            gender_args = "--sex %s" % (",".join(gender_chroms)) if gender_chroms else ""
            cmd = "goleft indexcov --directory {tmp_dir} {gender_args} -- {bam_file}"
            try:
                do.run(cmd.format(**locals()), "QC: goleft indexcov")
            except subprocess.CalledProcessError as msg:
                if not ("indexcov: no usable" in str(msg) or
                        ("indexcov: expected" in str(msg) and "sex chromosomes, found:" in str(msg))):
                    raise
            for out_file in out_files:
                orig_file = os.path.join(tmp_dir, os.path.basename(out_file))
                if utils.file_exists(orig_file):
                    utils.copy_plus(orig_file, out_file)
    # MultiQC needs non-gzipped/BED inputs so unpack the file
    out_bed = out_files[-1].replace(".bed.gz", ".tsv")
    if utils.file_exists(out_files[-1]) and not utils.file_exists(out_bed):
        with transaction.file_transaction(data, out_bed) as tx_out_bed:
            cmd = "gunzip -c %s > %s" % (out_files[-1], tx_out_bed)
            do.run(cmd, "Unpack indexcov BED file")
    out_files[-1] = out_bed
    return [x for x in out_files if utils.file_exists(x)]
Ejemplo n.º 3
0
def run(bam_file, data, out_dir):
    """Run coverage QC analysis
    """
    out = dict()

    out_dir = utils.safe_makedir(out_dir)
    if dd.get_coverage(data) and dd.get_coverage(data) not in ["None"]:
        merged_bed_file = bedutils.clean_file(dd.get_coverage_merged(data),
                                              data,
                                              prefix="cov-",
                                              simple=True)
        target_name = "coverage"
    elif dd.get_coverage_interval(data) != "genome":
        merged_bed_file = dd.get_variant_regions_merged(data)
        target_name = "variant_regions"
    else:
        merged_bed_file = None
        target_name = "genome"

    avg_depth = cov.get_average_coverage(target_name, merged_bed_file, data)
    if target_name == "coverage":
        out_files = cov.coverage_region_detailed_stats(target_name,
                                                       merged_bed_file, data,
                                                       out_dir)
    else:
        out_files = []

    out['Avg_coverage'] = avg_depth

    samtools_stats_dir = os.path.join(out_dir, os.path.pardir, 'samtools')
    from bcbio.qc import samtools
    samtools_stats = samtools.run(bam_file, data,
                                  samtools_stats_dir)["metrics"]

    out["Total_reads"] = total_reads = int(samtools_stats["Total_reads"])
    out["Mapped_reads"] = mapped = int(samtools_stats["Mapped_reads"])
    out["Mapped_paired_reads"] = int(samtools_stats["Mapped_paired_reads"])
    out['Duplicates'] = dups = int(samtools_stats["Duplicates"])

    if total_reads:
        out["Mapped_reads_pct"] = 100.0 * mapped / total_reads
    if mapped:
        out['Duplicates_pct'] = 100.0 * dups / mapped

    if dd.get_coverage_interval(data) == "genome":
        mapped_unique = mapped - dups
    else:
        mapped_unique = readstats.number_of_mapped_reads(data,
                                                         bam_file,
                                                         keep_dups=False)
    out['Mapped_unique_reads'] = mapped_unique

    if merged_bed_file:
        ontarget = readstats.number_of_mapped_reads(data,
                                                    bam_file,
                                                    keep_dups=False,
                                                    bed_file=merged_bed_file,
                                                    target_name=target_name)
        out["Ontarget_unique_reads"] = ontarget
        if mapped_unique:
            out["Ontarget_pct"] = 100.0 * ontarget / mapped_unique
            out['Offtarget_pct'] = 100.0 * (mapped_unique -
                                            ontarget) / mapped_unique
            if dd.get_coverage_interval(data) != "genome":
                # Skip padded calculation for WGS even if the "coverage" file is specified
                # the padded statistic makes only sense for exomes and panels
                padded_bed_file = bedutils.get_padded_bed_file(
                    out_dir, merged_bed_file, 200, data)
                ontarget_padded = readstats.number_of_mapped_reads(
                    data,
                    bam_file,
                    keep_dups=False,
                    bed_file=padded_bed_file,
                    target_name=target_name + "_padded")
                out["Ontarget_padded_pct"] = 100.0 * ontarget_padded / mapped_unique
        if total_reads:
            out['Usable_pct'] = 100.0 * ontarget / total_reads

    indexcov_files = _goleft_indexcov(bam_file, data, out_dir)
    out_files += [x for x in indexcov_files if x and utils.file_exists(x)]
    out = {"metrics": out}
    if len(out_files) > 0:
        out["base"] = out_files[0]
        out["secondary"] = out_files[1:]
    return out