def mapReadsAgainstSpadesContigs(infiles, outfile): ''' map reads against spades contigs ''' inf = infiles[0] to_cluster = True index_dir = os.path.dirname(outfile) if "agg" not in infiles[1]: genome = re.search( ".*R[0-9]*", infiles[0]).group(0) + ".filtered.contigs.fa" else: genome = "agg-agg-agg.filtered.contigs.fa" if infiles[1].endswith(".bt2") or infiles[1].endswith(".ebwt"): infile, reffile = infiles[0], os.path.join(index_dir, genome) + ".fa" m = PipelineMapping.Bowtie( executable=P.substituteParameters(**locals())["bowtie_executable"]) elif infiles[1].endswith("bwt"): genome = genome job_options = " -l mem_free=%s" % (PARAMS["bwa_memory"]) bwa_index_dir = index_dir bwa_mem_options = PARAMS["bwa_mem_options"] bwa_threads = PARAMS["bwa_threads"] m = PipelineMapping.BWAMEM(remove_non_unique=True) statement = m.build((inf,), outfile) P.run()
def mapBowtieAgainstTranscriptomeGSE65525(infiles, outfile): ''' map reads using Bowtie against transcriptome bowtie parameterised according to Allon et al 2015 except random reporting of alignments where more than one "best" exist (-M 1): -n 1 number of mismatches allowed -l 15 seed length -e 300 maxmimum permitted sum of sequence qualities at all mismatched positions -M 1 if more than one "best" alignment exist, report one at random --best report in best to worst order --strata only report reads falling into the best stratum ''' infile, reference = infiles job_threads = 2 job_options = "-l mem_free=1.9G" bowtie_options = "-n1 -l 15 -e 300 -M 1 --best --strata" bowtie_index_dir = os.path.abspath(os.path.dirname(reference)) genome = P.snip(os.path.basename(reference), ".1.ebwt") reffile = reference bowtie_threads = job_threads m = PipelineMapping.Bowtie(tool_options=bowtie_options, remove_non_unique=0, strip_sequence=0) statement = m.build((infile, ), outfile) P.run()
def run_mapping(infile, outfile): ''' Map reads with the specified read mapper ''' if PARAMS["mapper"] == "star": job_threads = PARAMS["star_threads"] job_memory = PARAMS["star_memory"] star_mapping_genome = PARAMS["star_genome"] or PARAMS["genome"] m = PipelineMapping.STAR( executable=P.substituteParameters(**locals())["star_executable"], strip_sequence=0) elif PARAMS["mapper"] == "bowtie": job_threads = PARAMS["bowtie_threads"] job_memory = PARAMS["bowtie_memory"] m = PipelineMapping.Bowtie(executable="bowtie", tool_options=PARAMS["bowtie_options"], strip_sequence=0) genome = PARAMS["bowtie_genome"] reffile = os.path.join(PARAMS["bowtie_index_dir"], PARAMS["bowtie_genome"] + ".fa") statement = m.build((infile, ), outfile) P.run()
def buildBAM(infile, outfile): '''map reads with bowtie''' track = P.snip(os.path.basename(outfile), ".bam") job_threads = PARAMS["bowtie_threads"] m = PipelineMapping.Bowtie() reffile = PARAMS["samtools_genome"] statement = m.build((infile, ), outfile) P.run()
def buildBAM(infile, outfile): '''map reads with bowtie''' to_cluster = True track = P.snip(os.path.basename(outfile), ".bam") job_options = "-pe dedicated %i -R y" % PARAMS["bowtie_threads"] m = PipelineMapping.Bowtie() reffile = PARAMS["samtools_genome"] statement = m.build((infile, ), outfile) P.run()
def buildBAM(infile, outfile, options): '''map reads with bowtie''' job_threads = PARAMS["bowtie_threads"] m = PipelineMapping.Bowtie() reffile = PARAMS["samtools_genome"] bowtie_options = options statement = m.build((infile,), outfile) # print(statement) P.run()
def alignReadsToTranscriptome(infile, outfile): '''map reads to transcriptome with bowtie''' track = P.snip(os.path.basename(outfile), ".bam") job_threads = PARAMS["bowtie_threads"] m = PipelineMapping.Bowtie() reffile = PARAMS["bowtie_transcriptome"] bowtie_options = PARAMS["bowtie_options"] statement = m.build((infile,), outfile) P.run()
def buildBAM(infile, outfile, options): '''map reads with bowtie''' to_cluster = True job_options = "-pe dedicated %i -R y" % PARAMS["bowtie_threads"] m = PipelineMapping.Bowtie() reffile = PARAMS["samtools_genome"] bowtie_options = options statement = m.build((infile,), outfile) # print(statement) P.run()
def mapReadsWithBowtieAgainstRayContigs(infile, outfile): ''' map reads against contigs with bowtie ''' PARAMS["bowtie_index_dir"] = "ray.dir" PARAMS["genome"] = TRACKS.getTracks(infile)[0].split(".")[0] infile, reffile = infile, os.path.join("ray.dir", TRACKS.getTracks(infile)[0]) m = PipelineMapping.Bowtie(executable=P.substituteParameters( **locals())["bowtie_executable"]) statement = m.build((infile, ), outfile) P.run()
def run_mapping(infile, outfile): ''' Map reads using the selected read mapper ''' job_threads = PARAMS["bowtie_threads"] job_memory = PARAMS["bowtie_memory"] m = PipelineMapping.Bowtie( executable="bowtie", tool_options=PARAMS["bowtie_options"], strip_sequence=0) genome = PARAMS["bowtie_genome"] reffile = os.path.join(PARAMS["bowtie_index_dir"], PARAMS["bowtie_genome"] + ".fa") statement = m.build((infile,), outfile) P.run()
def filterPhiX(infiles, outfile): ''' Use mapping to bowtie to remove any phiX mapping reads ''' infile, reffile = infiles outfile = P.snip(outfile, ".gz") bam_out = P.snip(infile, ".fastq.gz") + ".phix.bam" job_threads = PARAMS["phix_bowtie_threads"] job_memory = PARAMS["phix_bowtie_memory"] options = PARAMS["phix_bowtie_options"] + " --un %s" % outfile genome = PARAMS["phix_genome"] bowtie_threads = PARAMS["phix_bowtie_threads"] m = PipelineMapping.Bowtie(executable=PARAMS["phix_bowtie_exe"], strip_sequence=False, remove_non_unique=False, tool_options=options) statement = m.build((infile, ), bam_out) statement += "checkpoint; gzip %(outfile)s" P.run()