def _prep_subsampled_bams(data, work_dir):
"""Prepare a subsampled BAM file with discordants from samblaster and minimal correct pairs.
This attempts to minimize run times by pre-extracting useful reads mixed
with subsampled normal pairs to estimate paired end distributions:
https://groups.google.com/d/msg/delly-users/xmia4lwOd1Q/uaajoBkahAIJ
Subsamples correctly aligned reads to 100 million based on speedseq defaults and
evaluations on NA12878 whole genome data:
https://github.com/cc2qe/speedseq/blob/ca624ba9affb0bd0fb88834ca896e9122639ec94/bin/speedseq#L1102
XXX Currently not used as new versions of delly do not get good sensitivity
with downsampled BAMs.
"""
sr_bam, disc_bam = sshared.get_split_discordants(data, work_dir)
ds_bam = bam.downsample(
dd.get_align_bam(data),
data,
1e8,
read_filter="-F 'not secondary_alignment and proper_pair'",
always_run=True,
work_dir=work_dir)
out_bam = "%s-final%s" % utils.splitext_plus(ds_bam)
if not utils.file_exists(out_bam):
bam.merge([ds_bam, sr_bam, disc_bam], out_bam, data["config"])
bam.index(out_bam, data["config"])
return [out_bam]
def _prep_subsampled_bams(data, work_dir):
"""Prepare a subsampled BAM file with discordants from samblaster and minimal correct pairs.
This attempts to minimize run times by pre-extracting useful reads mixed
with subsampled normal pairs to estimate paired end distributions:
https://groups.google.com/d/msg/delly-users/xmia4lwOd1Q/uaajoBkahAIJ
Subsamples correctly aligned reads to 100 million based on speedseq defaults and
evaluations on NA12878 whole genome data:
https://github.com/cc2qe/speedseq/blob/ca624ba9affb0bd0fb88834ca896e9122639ec94/bin/speedseq#L1102
XXX Currently does not downsample as new versions do not get good sensitivity with
downsampled BAMs.
"""
full_bam, sr_bam, disc_bam = sshared.get_split_discordants(data, work_dir)
return [full_bam]
ds_bam = bam.downsample(full_bam, data, 1e8, read_filter="-F 'not secondary_alignment and proper_pair'",
always_run=True, work_dir=work_dir)
out_bam = "%s-final%s" % utils.splitext_plus(ds_bam)
if not utils.file_exists(out_bam):
bam.merge([ds_bam, sr_bam, disc_bam], out_bam, data["config"])
bam.index(out_bam, data["config"])
return [out_bam]
def cufflinks_assemble(*samples):
rnaseq_resources = samples[0][0]["genome_resources"]["rnaseq"]
config = samples[0][0]["config"]
dirs = samples[0][0]["dirs"]
gtf_file = rnaseq_resources.get("transcripts", None)
ref_file = samples[0][0]["sam_ref"]
bam_files = [data[0]['work_bam'] for data in samples]
num_cores = config["algorithm"].get("num_cores", 1)
out_dir = os.path.join(dirs["work"], "assembly")
safe_makedir(out_dir)
merged_file = os.path.join(out_dir, "merged.bam")
merged_file = bam.merge(bam_files, merged_file, config)
assembly_dir = cufflinks.assemble(merged_file, ref_file, gtf_file,
num_cores, out_dir)
transcripts = [os.path.join(assembly_dir, "assembly", "transcripts.gtf")]
merged_gtf = cufflinks.merge(transcripts, ref_file, gtf_file, num_cores)
for data in samples:
data[0]['assembly'] = assembly_dir
return samples
def merge_unmapped(mapped_sam, unmapped_bam, config):
merged_bam = os.path.join(os.path.dirname(mapped_sam), "merged.bam")
bam_file = bam.sam_to_bam(mapped_sam, config)
if not file_exists(merged_bam):
merged_bam = bam.merge([bam_file, unmapped_bam], merged_bam, config)
return merged_bam
def merge_unmapped(mapped_sam, unmapped_bam, config):
merged_bam = os.path.join(os.path.dirname(mapped_sam), "merged.bam")
bam_file = bam.sam_to_bam(mapped_sam, config)
if not file_exists(merged_bam):
merged_bam = bam.merge([bam_file, unmapped_bam], merged_bam, config)
return merged_bam
