def rare_variants_famseq(self, selected_vcf, vcf_out):
"""Call rare variants with pedigree information using FamSeq"""
# e.g. FamSeq vcf -vcfFile ../TestData/test.vcf -pedFile ../TestData/fam01.ped -output test.FamSeq.vcf -v
command = "FamSeq vcf -vcfFile {selected_vcf} -pedFile {ped_file} -output {vcf_out}".format(
selected_vcf=selected_vcf, ped_file=self.famseq_ped_file, vcf_out=vcf_out
)
run_stage(self.state, "rare_variants_famseq", command)
def concatenate_vcfs(self, vcf_files_in, vcf_out):
if (len(vcf_files_in) > 200):
merge_commands = []
temp_merge_outputs = []
for n in range(0,
int(math.ceil(float(len(vcf_files_in)) / 200.0))):
start = n * 200
filelist = vcf_files_in[start:start + 200]
filelist_command = ' '.join([vcf for vcf in filelist])
temp_merge_filename = vcf_out.rstrip(
'.vcf') + ".temp_{start}.vcf".format(start=str(start))
command1 = 'bcftools merge -O z -o {vcf_out} {join_vcf_files} && bcftools index -t -f {vcf_out}; '.format(
vcf_out=temp_merge_filename,
join_vcf_files=filelist_command)
merge_commands.append(command1)
temp_merge_outputs.append(temp_merge_filename)
final_merge_vcfs = ' '.join([vcf for vcf in temp_merge_outputs])
command2 = 'bcftools merge -O z -o {vcf_out} {join_vcf_files} '.format(
vcf_out=vcf_out, join_vcf_files=final_merge_vcfs)
merge_commands.append(command2)
final_command = ''.join(merge_commands)
else:
filelist = ' '.join([vcf for vcf in vcf_files_in])
final_command = 'bcftools merge -O z -o {vcf_out} {vcf_files} '.format(
vcf_out=vcf_out, vcf_files=filelist)
run_stage(self.state, 'concatenate_vcfs', final_command)
def clip_bam(self, bam_in, sorted_bam_out):
'''Clip the BAM file using Bamclipper'''
bamclipper_args = '{bamclipper} -b {bam_in} -p {primer_bedpe_file} -n 1'.format(
bamclipper=self.bamclipper,
bam_in=bam_in,
primer_bedpe_file=self.primer_bedpe_file)
run_stage(self.state, 'clip_bam', bamclipper_args)
def extract_split_read_alignments(self, bam_in, splitters_bam_out):
'''Extract the split-read alignments using samtools'''
command = ('samtools view -h {input_bam} | ' \
'extractSplitReads_BwaMem -i stdin | ' \
'samtools view -Sb - > {output_bam}'
.format(input_bam=bam_in, output_bam=splitters_bam_out))
run_stage(self.state, 'extract_split_read_alignments', command)
def apply_undr_rover(self, inputs, vcf_output, sample_id):
'''Apply undr_rover to call variants from paired end fastq files'''
fastq_read1_in, fastq_read2_in = inputs
cores = self.get_stage_options('apply_undr_rover', 'cores')
safe_make_dir('variants/undr_rover')
safe_make_dir('variants/undr_rover/coverdir')
coverdir = "variants/undr_rover/coverdir"
coverfile = sample_id + ".coverage"
command = 'undr_rover --primer_coords {coord_file} ' \
'--primer_sequences {primer_file} ' \
'--reference {reference} ' \
'--out {vcf_output} ' \
'--coverfile {coverdir}/{coverfile} ' \
'--proportionthresh {proportionthresh} ' \
'--absthresh {absthresh} ' \
'--max_variants {maxvariants} ' \
'{fastq_read1} {fastq_read2}'.format(
coord_file=self.coord_file, primer_file=self.primer_file,
reference=self.reference,
vcf_output=vcf_output,
coverdir=coverdir,
proportionthresh=self.proportionthresh,
absthresh=self.absthresh,
maxvariants=self.maxvariants,
coverfile=coverfile,
fastq_read1=fastq_read1_in,
fastq_read2=fastq_read2_in)
run_stage(self.state, 'apply_undr_rover', command)
def apply_cat_vcf(self, inputs, vcf_out):
'''Concatenate and sort undr_rover VCF files for downstream analysis'''
vcfs = ' '.join([vcf for vcf in inputs])
# safe_make_dir('variants')
command = 'vcf-concat {vcfs} | vcf-sort -c | bgzip -c > {vcf_out} '.format(
vcfs=vcfs, vcf_out=vcf_out)
run_stage(self.state, 'apply_cat_vcf', command)
def vt_decompose_normalise(self, vcf_in, vcf_out):
'''Decompose multiallelic sites and normalise representations'''
command = "vt decompose -s {vcf_in} | vt normalize -r {reference} -o " \
"{vcf_out} -".format(reference=self.reference,
vcf_in=vcf_in,
vcf_out=vcf_out)
run_stage(self.state, 'vt_decompose_normalise', command)
def apply_undr_rover(self, input, vcf_output, sample_id):
'''Apply undr_rover to call variants from paired end fastq files'''
fastq_read1_in = 'fastqs/' + input[11:-20] + '_R1_001.fastq.gz'
fastq_read2_in = 'fastqs/' + input[11:-20] + '_R2_001.fastq.gz'
coverdir = "variants/undr_rover/coverdir"
coverfile = sample_id + ".coverage"
if "QC" in fastq_read1_in:
primer_file = self.primer_file_QC
interval_file = self.interval_file_QC
else:
primer_file = self.primer_file_default
interval_file = self.interval_file
command = 'undr_rover --primer_coords {coord_file} ' \
'--primer_sequences {primer_file} ' \
'--reference {reference} ' \
'--out {vcf_output} ' \
'--coverfile {coverdir}/{coverfile} ' \
'--proportionthresh {proportionthresh} ' \
'--absthresh {absthresh} ' \
'--max_variants {maxvariants} ' \
'--fast --snvthresh 10 ' \
'{fastq_read1} {fastq_read2}'.format(
coord_file=interval_file, primer_file=primer_file,
reference=self.reference,
vcf_output=vcf_output,
coverdir=coverdir,
proportionthresh=self.proportionthresh,
absthresh=self.absthresh,
maxvariants=self.maxvariants,
coverfile=coverfile,
fastq_read1=fastq_read1_in,
fastq_read2=fastq_read2_in)
run_stage(self.state, 'apply_undr_rover', command)
def align_bwa(self, inputs, bam_out, sample_id, lib):
'''Align the paired end fastq files to the reference genome using bwa'''
fastq_read1_in, fastq_read2_in = inputs
cores = self.get_stage_options('align_bwa', 'cores')
read_group = '"@RG\\tID:{sample}\\tSM:{sample}\\tPU:lib1\\tPL:Illumina"' \
.format(sample=sample_id)
if "QC" in fastq_read1_in:
primer_bedpe_file = self.primer_bedpe_file_QC
else:
primer_bedpe_file = self.primer_bedpe_file_default
command = 'bwa mem -M -t {cores} -R {read_group} {reference} {fastq_read1} {fastq_read2} ' \
'| {bamclipper} -i -p {primer_bedpe_file} -n {cores} ' \
'| samtools view -u -h -q 1 -f 2 -F 4 -F 8 -F 256 - ' \
'| samtools sort -@ {cores} -o {bam}; samtools index {bam}'.format(
cores=cores,
read_group=read_group,
fastq_read1=fastq_read1_in,
fastq_read2=fastq_read2_in,
reference=self.reference,
bamclipper=self.bamclipper,
primer_bedpe_file=primer_bedpe_file,
bam=bam_out)
run_stage(self.state, 'align_bwa', command)
def combine_gvcf_gatk(self, vcf_files_in, vcf_out):
'''Combine G.VCF files for all samples using GATK'''
merge_commands = []
temp_merge_outputs = []
for n in range(0, int(math.ceil(float(len(vcf_files_in)) / 200.0))):
start = n * 200
filelist = vcf_files_in[start:start + 200]
filelist_command = ' '.join(
['--variant ' + vcf for vcf in filelist])
temp_merge_filename = vcf_out.rstrip(
'.vcf') + ".temp_{start}.vcf".format(start=str(start))
gatk_args_full = "java -Xmx{mem}g -jar {jar_path} -T CombineGVCFs -R {reference} " \
"--disable_auto_index_creation_and_locking_when_reading_rods " \
"{g_vcf_files} -o {vcf_out}; ".format(reference=self.reference,
jar_path=self.gatk_jar,
mem=self.state.config.get_stage_options('combine_gvcf_gatk', 'mem'),
g_vcf_files=filelist_command,
vcf_out=temp_merge_filename)
merge_commands.append(gatk_args_full)
temp_merge_outputs.append(temp_merge_filename)
final_merge_vcfs = ' '.join(
['--variant ' + vcf for vcf in temp_merge_outputs])
gatk_args_full_final = "java -Xmx{mem}g -jar {jar_path} -T CombineGVCFs -R {reference} " \
"--disable_auto_index_creation_and_locking_when_reading_rods " \
"{g_vcf_files} -o {vcf_out}".format(reference=self.reference,
jar_path=self.gatk_jar,
mem=self.state.config.get_stage_options('combine_gvcf_gatk', 'mem'),
g_vcf_files=final_merge_vcfs,
vcf_out=vcf_out)
merge_commands.append(gatk_args_full_final)
final_command = ''.join(merge_commands)
run_stage(self.state, 'combine_gvcf_gatk', final_command)
def apply_bcftools(self, mpileup_in, vcf_out):
'''Bcftools call variants'''
mpileup_in = mpileup_in
# mpileup_in = ' '.join([vcf for vcf in vcf_files_in])
command = 'bcftools call -vmO v -o {vcf_out} {mpileup_in}'.format(
vcf_out=vcf_out, mpileup_in=mpileup_in)
run_stage(self.state, 'apply_bcftools', command)
def extract_split_read_alignments(self, bam_in, splitters_bam_out):
'''Extract the split-read alignments using samtools'''
command = ('samtools view -h {input_bam} | ' \
'extractSplitReads_BwaMem -i stdin | ' \
'samtools view -Sb - > {output_bam}'
.format(input_bam=bam_in, output_bam=splitters_bam_out))
run_stage(self.state, 'extract_split_read_alignments', command)
def target_coverage_bamutil_interval(self, bam_in, coverage_out):
'''Calculate target coverage using bamutil'''
command = 'bam stats --basic --in {bam_in} --regionList {fragment_bed} &> {coverage_out}'.format(
bam_in=bam_in,
fragment_bed=self.fragment_bed,
coverage_out=coverage_out)
run_stage(self.state, 'target_coverage_bamutil_interval', command)
def extract_genes_bedtools(self, bam_in, bam_out):
'''Extract MMR genes from the sorted BAM file'''
bed_file = self.state.config.get_stage_option('extract_genes_bedtools',
'bed')
command = 'bedtools intersect -abam {bam_in} -b {bed_file} > {bam_out}' \
.format(bam_in=bam_in, bed_file=bed_file, bam_out=bam_out)
run_stage(self.state, 'extract_genes_bedtools', command)
def fastq_to_fasta(self, fastq_in, fasta_out):
'''Convert FASTQ file to FASTA'''
# -n flag says keep reads with 'N' (unknown) bases, otherwise
# they would have been discarded
# -Q33 means use Illumina quality scores
command = 'zcat {fastq_in} | fastq_to_fasta -n -Q33 -o {fasta_out}'.format(fastq_in=fastq_in, fasta_out=fasta_out)
run_stage(self.state, 'fastq_to_fasta', command)
def apply_bcf(self, inputs, vcf_out):
'''Apply BCF'''
vcf_in = inputs
cores = self.get_stage_options('apply_bcf', 'cores')
command = "bcftools filter -e \"ALT='*'\" {vcf_in} > {vcf_out}".format(
cores=cores, vcf_in=vcf_in, vcf_out=vcf_out)
run_stage(self.state, 'apply_bcf', command)
def apply_vep(self, inputs, vcf_out):
'''Apply VEP'''
vcf_in = inputs
cores = self.get_stage_options('apply_vep', 'cores')
vep_command = "vep --cache --dir_cache {other_vep} " \
"--assembly GRCh37 --refseq --offline " \
"--fasta {reference} " \
"--sift b --polyphen b --symbol --numbers --biotype --total_length --hgvs --format vcf " \
"--vcf --force_overwrite --flag_pick --no_stats " \
"--custom {brcaexpath},brcaex,vcf,exact,0,Clinical_significance_ENIGMA," \
"Comment_on_clinical_significance_ENIGMA,Date_last_evaluated_ENIGMA," \
"Pathogenicity_expert,HGVS_cDNA,HGVS_Protein,BIC_Nomenclature " \
"--custom {gnomadpath},gnomAD,vcf,exact,0,AF_NFE,AN_NFE " \
"--custom {revelpath},RVL,vcf,exact,0,REVEL_SCORE " \
"--plugin MaxEntScan,{maxentscanpath} " \
"--plugin ExAC,{exacpath},AC,AN " \
"--plugin dbNSFP,{dbnsfppath},REVEL_score,REVEL_rankscore " \
"--plugin dbscSNV,{dbscsnvpath} " \
"--plugin CADD,{caddpath} " \
"--fork {cores} " \
"-i {vcf_in} " \
"-o {vcf_out}".format(other_vep=self.other_vep,
cores=cores,
vcf_out=vcf_out,
vcf_in=vcf_in,
reference=self.reference,
brcaexpath=self.brcaex,
gnomadpath=self.gnomad,
revelpath=self.revel,
maxentscanpath=self.maxentscan,
exacpath=self.exac,
dbnsfppath=self.dbnsfp,
dbscsnvpath=self.dbscsnv,
caddpath=self.cadd)
run_stage(self.state, 'apply_vep', vep_command)
def genotype_svtyper(self, inputs, vcf_out):
'''Call genotypes on lumpy output using SVTyper'''
vcf_in, [sample_bam, splitters_bam] = inputs
command = 'svtyper -B {sample_bam} -S {splitters_bam} ' \
'-i {vcf_in} -o {vcf_out}' \
.format(sample_bam=sample_bam, splitters_bam=splitters_bam,
vcf_in=vcf_in, vcf_out=vcf_out)
run_stage(self.state, 'genotype_svtyper', command)
def fastq_to_fasta(self, fastq_in, fasta_out):
'''Convert FASTQ file to FASTA'''
# -n flag says keep reads with 'N' (unknown) bases, otherwise
# they would have been discarded
# -Q33 means use Illumina quality scores
command = 'zcat {fastq_in} | fastq_to_fasta -n -Q33 -o {fasta_out}'.format(
fastq_in=fastq_in, fasta_out=fasta_out)
run_stage(self.state, 'fastq_to_fasta', command)
def filter_stats(self, txt_in, txt_out):
'''filter the summary file to make a 'passed' file'''
# Only mark samples as pass if >= 80% of target is covered at at least 10X
# Set to 0 for now since I want to make everything pass
awk_comm = "{if($8 >= 0){print $1\".sorted.locatit.bam\"}}"
command = "awk '{awk_comm}' {summary_file} > {final_file}".format(
awk_comm=awk_comm, summary_file=txt_in, final_file=txt_out)
run_stage(self.state, 'filter_stats', command)
def structural_variants_lumpy(self, inputs, vcf_out):
'''Call structural variants with lumpy'''
sample_bam, [splitters_bam, discordants_bam] = inputs
command = 'lumpyexpress -B {sample_bam} -S {splitters_bam} ' \
'-D {discordants_bam} -o {vcf}' \
.format(sample_bam=sample_bam, splitters_bam=splitters_bam,
discordants_bam=discordants_bam, vcf=vcf_out)
run_stage(self.state, 'structural_variants_lumpy', command)
def apply_multicov(self, bam_in, multicov):
'''Samtools mpileup'''
# bam_in = bam_in
bams = ' '.join([bam for bam in bam_in])
safe_make_dir('coverage')
command = 'bedtools multicov -bams {bams} -bed {target_bed} > {multicov}'.format(
bams=bams, target_bed=self.target_bed, multicov=multicov)
run_stage(self.state, 'apply_multicov', command)
def apply_summarize_picard(self, input, output):
'''Summarize picard coverage'''
input = input
# bams = ' '.join([bam for bam in bam_in])
# safe_make_dir('variants')
command = 'python coverage_summary.py > {output} '.format(
output=output)
run_stage(self.state, 'apply_summarize_picard', command)
def rare_variants_famseq(self, selected_vcf, vcf_out):
'''Call rare variants with pedigree information using FamSeq'''
# e.g. FamSeq vcf -vcfFile ../TestData/test.vcf -pedFile ../TestData/fam01.ped -output test.FamSeq.vcf -v
# FamSeq methods - 1: Bayesian network; 2: Elston-Stewart algorithm; 3: MCMC
command = "PATH=/vlsci/LSC0007/shared/jessica_testing/software/FamSeq/src/:$PATH ; " \
"FamSeq vcf -method 2 -vcfFile {selected_vcf} -pedFile {ped_file} -output {vcf_out}".format(selected_vcf=selected_vcf,
ped_file=self.famseq_ped_file, vcf_out=vcf_out)
run_stage(self.state, 'rare_variants_famseq', command)
def structural_variants_lumpy(self, inputs, vcf_out):
'''Call structural variants with lumpy'''
sample_bam, [splitters_bam, discordants_bam] = inputs
command = 'lumpyexpress -B {sample_bam} -S {splitters_bam} ' \
'-D {discordants_bam} -o {vcf}' \
.format(sample_bam=sample_bam, splitters_bam=splitters_bam,
discordants_bam=discordants_bam, vcf=vcf_out)
run_stage(self.state, 'structural_variants_lumpy', command)
def generate_amplicon_metrics(self, bam_in, txt_out, sample):
'''Generate depth information for each amplicon and sample for heatmap plotting'''
command = 'bedtools coverage -f 5E-1 -a {bed_intervals} -b {bam_in} | ' \
'sed "s/$/ {sample}/g" > {txt_out}'.format(bed_intervals=self.interval_file,
bam_in=bam_in,
sample=sample,
txt_out=txt_out)
run_stage(self.state, 'generate_amplicon_metrics', command)
def translocations_delly(self, bams_in, vcf_out):
'''Call translocatins with delly'''
bams_args = ' '.join(bams_in)
threads = self.state.config.get_stage_option('structural_variants_delly', 'cores')
exclude = self.state.config.get_stage_option('structural_variants_delly', 'exclude')
command = 'OMP_NUM_THREADS={threads} delly -t TRA -x {exclude} -o {vcf_out} -g {reference} {bams}' \
.format(threads=threads, exclude=exclude, vcf_out=vcf_out, reference=self.reference, bams=bams_args)
run_stage(self.state, 'structural_variants_delly', command)
def genotype_svtyper(self, inputs, vcf_out):
'''Call genotypes on lumpy output using SVTyper'''
vcf_in, [sample_bam, splitters_bam] = inputs
command = 'svtyper -B {sample_bam} -S {splitters_bam} ' \
'-i {vcf_in} -o {vcf_out}' \
.format(sample_bam=sample_bam, splitters_bam=splitters_bam,
vcf_in=vcf_in, vcf_out=vcf_out)
run_stage(self.state, 'genotype_svtyper', command)
def apply_samtools_mpileup(self, bam_in, mpileup_out_bcf):
'''Samtools mpileup'''
# bam_in = bam_in
bams = ' '.join([bam for bam in bam_in])
safe_make_dir('variants')
command = 'samtools mpileup -t DP,AD,ADF,ADR,SP,INFO/AD,INFO/ADF,INFO/ADR -go {mpileup_out_bcf} ' \
'-f {reference} {bams}'.format(
mpileup_out_bcf=mpileup_out_bcf,reference=self.reference,bams=bams)
run_stage(self.state, 'apply_samtools_mpileup', command)
def alignment_stats_bamtools(self, bam_in, outputs):
'''Get alignment stats using Bamtools'''
command = "bamtools stats -in {bam} > {out}".format(bam=bam_in, out=outputs)
run_stage(self.state, 'alignment_stats_bamtools', command)
def snpEff_annotate(self, vcf_in, outputs):
'''Get annotation results using snpEff'''
command = "SnpEff -lof {vcf_in} > {out}".format(vcf_in=vcf_in,out=outputs)
run_stage(self.state, 'snpEff_annotation_tools', command)
def apply_homopolymer_ann(self, inputs, vcf_out):
'''Apply HomopolymerRun annotation to undr_rover output'''
vcf_in = inputs
# safe_make_dir('variants')
command = "echo \"##INFO=<ID=HRUN,Number=1,Type=String,Description=\"HRun\">\" > header.tmp; "\
"bcftools annotate -a {hrfile} -c CHROM,FROM,TO,HRUN " \
"-h header.tmp " \
"{vcf_in} > {vcf_out}".format(hrfile=self.hrfile,vcf_in=vcf_in,vcf_out=vcf_out)
run_stage(self.state, 'apply_cat_vcf', command)
def apply_vt(self, inputs, vcf_out):
'''Apply NORM'''
vcf_in = inputs
cores = self.get_stage_options('apply_vt', 'cores')
vt_command = "{vt_path} decompose -s {vcf_in} - | {vt_path2} normalize -r {reference} " \
"-o {vcf_out} - ".format(
vt_path=self.vt_path, vcf_in=vcf_in, vt_path2=self.vt_path, reference=self.reference,
vcf_out=vcf_out)
run_stage(self.state, 'apply_vt', vt_command)
def read_samples(self, input_pth, outputs):
'''Reads the list of pass samples and touches files accordingly
in the alignments/pass_samples folder'''
with open(input_pth, 'r') as inputf:
pass_files = inputf.read().split('\n')
command_l = []
for f in pass_files:
command_l.append("metrics/pass_samples/{}".format(f))
command = 'touch {}'.format(' '.join(command_l))
run_stage(self.state, 'read_samples', command)
def apply_vcfanno(self, inputs, vcf_out):
'''Apply anno'''
vcf_in = inputs
#cores = self.get_stage_options('apply_snpeff', 'cores')
anno_command = "./vcfanno_linux64 -lua {annolua} {anno} {vcf_in} > {vcf_out}".format(
annolua=self.annolua,
anno=self.anno,
vcf_in=vcf_in,
vcf_out=vcf_out)
run_stage(self.state, 'apply_vcfanno', anno_command)
def translocations_delly(self, bams_in, vcf_out):
'''Call translocatins with delly'''
bams_args = ' '.join(bams_in)
threads = self.state.config.get_stage_option(
'structural_variants_delly', 'cores')
exclude = self.state.config.get_stage_option(
'structural_variants_delly', 'exclude')
command = 'OMP_NUM_THREADS={threads} delly -t TRA -x {exclude} -o {vcf_out} -g {reference} {bams}' \
.format(threads=threads, exclude=exclude, vcf_out=vcf_out, reference=self.reference, bams=bams_args)
run_stage(self.state, 'structural_variants_delly', command)
def apply_snpeff(self, inputs, vcf_out):
'''Apply SnpEFF'''
vcf_in = inputs
#cores = self.get_stage_options('apply_snpeff', 'cores') apply_snpeff
# mem = int(self.state.config.get_stage_options(stage, 'mem'))
mem = int(self.get_stage_options('apply_snpeff', 'mem')) - 2
snpeff_command = "java -Xmx{mem}g -jar {snpeff_path} eff -c {snpeff_conf} " \
"-canon GRCh37.75 {vcf_in} | bgzip -c > {vcf_out}".format(
mem=mem, snpeff_path=self.snpeff_path, snpeff_conf=self.snpeff_conf,
vcf_in=vcf_in, vcf_out=vcf_out)
run_stage(self.state, 'apply_snpeff', snpeff_command)
def sort_bam_sambamba(self, bam_in, sorted_bam_out):
'''Sort the reads in a bam file using sambamba'''
cores = self.state.config.get_stage_option('sort_bam_sambamba', 'cores')
# Get the tmp directory
tmp = self.state.config.get_option('tmp')
# Get the amount of memory requested for the job
mem = int(self.state.config.get_stage_option('sort_bam_sambamba', 'mem'))
mem_limit = max(mem - 4, 1)
command = 'sambamba sort --nthreads={cores} --memory-limit={mem}GB --tmpdir={tmp} --out={output_bam} {input_bam}' \
.format(cores=cores, mem=mem_limit, tmp=tmp, input_bam=bam_in, output_bam=sorted_bam_out)
run_stage(self.state, 'sort_bam_sambamba', command)
def structural_variants_pindel(self, inputs, output):
'''Call structural variants with pindel'''
bam_in, [config_in, reference_in] = inputs
cores = self.state.config.get_stage_option(
'structural_variants_pindel', 'cores')
command = 'pindel -T {threads} -f {reference} -i {config} -c ALL -o {output}'.format(
threads=cores,
reference=reference_in,
config=config_in,
output=output)
run_stage(self.state, 'structural_variants_pindel', command)
def run_connor(self, bam_in, bam_out):
'''run connor on bam file'''
command = 'connor --force -f {CONSENSUS_FREQ_THRESHOLD} ' \
'-s {MIN_FAMILY_SIZE_THRESHOLD} ' \
'-d {UMT_DISTANCE_THRESHOLD} ' \
'{bam_in} {bam_out}'.format(
CONSENSUS_FREQ_THRESHOLD=self.CONSENSUS_FREQ_THRESHOLD,
MIN_FAMILY_SIZE_THRESHOLD=self.MIN_FAMILY_SIZE_THRESHOLD,
UMT_DISTANCE_THRESHOLD=self.UMT_DISTANCE_THRESHOLD,
bam_in=bam_in,bam_out=bam_out)
run_stage(self.state, 'run_connor', command)
def align_bwa(self, inputs, bam_out, sample_id):
'''Align the paired end fastq files to the reference genome using bwa'''
fastq_read1_in, fastq_read2_in = inputs
cores = self.get_stage_options('align_bwa', 'cores')
read_group = '"@RG\tID:{sample}\tSM:{sample}\tPL:Illumina"'.format(sample=sample_id)
command = 'bwa mem -t {cores} -R {read_group} {reference} {fastq_read1} {fastq_read2} ' \
'| samtools view -b -h -o {bam} -' \
.format(cores=cores,
read_group=read_group,
fastq_read1=fastq_read1_in,
fastq_read2=fastq_read2_in,
reference=self.reference,
bam=bam_out)
run_stage(self.state, 'align_bwa', command)
def structural_variants_socrates(self, bam_in, variants_out, sample_dir):
'''Call structural variants with Socrates'''
threads = self.state.config.get_stage_option('structural_variants_socrates', 'cores')
# jvm_mem is in gb
jvm_mem = self.state.config.get_stage_option('structural_variants_socrates', 'jvm_mem')
bowtie2_ref_dir = self.state.config.get_stage_option('structural_variants_socrates', 'bowtie2_ref_dir')
output_dir = os.path.join(sample_dir, 'socrates')
safe_make_dir(output_dir)
command = \
'''
cd {output_dir}
export _JAVA_OPTIONS='-Djava.io.tmpdir={output_dir}'
Socrates all -t {threads} --bowtie2_threads {threads} --bowtie2_db {bowtie2_ref_dir} --jvm_memory {jvm_mem}g {bam}
'''.format(output_dir=output_dir, threads=threads, bowtie2_ref_dir=bowtie2_ref_dir, jvm_mem=jvm_mem, bam=bam_in)
run_stage(self.state, 'structural_variants_socrates', command)
def align_bwa(self, inputs, bam_out, read_id, lib, lane, sample_id):
# def align_bwa(self, inputs, bam_out, sample_id):
'''Align the paired end fastq files to the reference genome using bwa'''
fastq_read1_in, fastq_read2_in = inputs
cores = self.get_stage_options('align_bwa', 'cores')
safe_make_dir('alignments/{sample}'.format(sample=sample_id))
read_group = '"@RG\\tID:{readid}\\tSM:{sample}\\tPU:lib1\\tLN:{lane}\\tPL:Illumina"' \
.format(readid=read_id, lib=lib, lane=lane, sample=sample_id)
command = 'bwa mem -t {cores} -R {read_group} {reference} {fastq_read1} {fastq_read2} ' \
'| samtools view -b -h -o {bam} -' \
.format(cores=cores,
read_group=read_group,
fastq_read1=fastq_read1_in,
fastq_read2=fastq_read2_in,
reference=self.reference,
bam=bam_out)
run_stage(self.state, 'align_bwa', command)
def align_bwa(self, inputs, bam_out, sample, id):
"""Align the paired end fastq files to the reference genome using bwa"""
fastq_read1_in, fastq_read2_in = inputs
cores = self.get_stage_options("align_bwa", "cores")
read_group = '"@RG\\tID:{id}\\tSM:{sample}\\tPL:Illumina"'.format(sample=sample, id=id)
command = (
"bwa mem -t {cores} -R {read_group} {reference} {fastq_read1} {fastq_read2} "
"| samtools view -b -h -o {bam} -".format(
cores=cores,
read_group=read_group,
fastq_read1=fastq_read1_in,
fastq_read2=fastq_read2_in,
reference=self.reference,
bam=bam_out,
)
)
safe_make_dir("results/alignments/{sample}".format(sample=sample))
run_stage(self.state, "align_bwa", command)
def align_bwa(self, inputs, bam_out, sample):
'''Align the paired end fastq files to the reference genome using bwa'''
fastq_read1_in, fastq_read2_in = inputs
# Get the read group information for this sample from the configuration file
read_group = self.state.config.get_read_group(sample)
# Get the number of cores to request for the job, this translates into the
# number of threads to give to bwa's -t option
cores = self.state.config.get_stage_option('align_bwa', 'cores')
# Run bwa and pipe the output through samtools view to generate a BAM file
command = 'bwa mem -t {cores} -R "{read_group}" {reference} {fastq_read1} {fastq_read2} ' \
'| samtools view -S -b - > {bam}' \
.format(cores=cores,
read_group=read_group,
fastq_read1=fastq_read1_in,
fastq_read2=fastq_read2_in,
reference=self.reference,
bam=bam_out)
run_stage(self.state, 'align_bwa', command)
def peak_picker_hires(self, mzml_in, mzml_out):
'''Executes the peak picking with high_res algorithm'''
cores = self.state.config.get_stage_option('baseline_filter', 'cores')
command = "PeakPickerHiRes -threads {cores} -in {mzml_in} -out {mzml_out}".format(cores=cores, mzml_in=mzml_in, mzml_out=mzml_out)
run_stage(self.state, 'peak_picker_hires', command)
def baseline_filter(self, mzml_in, mzml_out):
'''Executes the top-hat filter to remove the baseline of an MS experiment.'''
cores = self.state.config.get_stage_option('baseline_filter', 'cores')
command = "BaselineFilter -threads {cores} -in {mzml_in} -out {mzml_out}".format(cores=cores, mzml_in=mzml_in, mzml_out=mzml_out)
run_stage(self.state, 'baseline_filter', command)
def noise_filter_sgolay(self, mzml_in, mzml_out):
'''Filter noise using Savitzky Golay'''
cores = self.state.config.get_stage_option('noise_filter_sgolay', 'cores')
command = "NoiseFilterSGolay -threads {cores} -in {mzml_in} -out {mzml_out}".format(cores=cores, mzml_in=mzml_in, mzml_out=mzml_out)
run_stage(self.state, 'noise_filter_sgolay', command)
def resample(self, mzml_in, mzml_out):
'''Resample MZML file to new sampling rate'''
cores = self.state.config.get_stage_option('resample', 'cores')
rate = self.state.config.get_stage_option('resample', 'rate')
command = "Resampler -sampling_rate {rate} -threads {cores} -in {mzml_in} -out {mzml_out}".format(rate=rate, cores=cores, mzml_in=mzml_in, mzml_out=mzml_out)
run_stage(self.state, 'resample', command)
def extract_discordant_alignments(self, bam_in, discordants_bam_out):
'''Extract the discordant paired-end alignments using samtools'''
command = 'samtools view -b -F 1294 {input_bam} > {output_bam}' \
.format(input_bam=bam_in, output_bam=discordants_bam_out)
run_stage(self.state, 'extract_discordant_alignments', command)
def extract_chromosomes_samtools(self, bam_in, bam_out):
'''Extract selected chomosomes from the bam files'''
command = 'samtools view -h -b {bam_in} chr2 chr3 chr7 > {bam_out}' \
.format(bam_in=bam_in, bam_out=bam_out)
run_stage(self.state, 'extract_chromosomes_samtools', command)
def bamtools_stats(self, bam_in, stats_out):
'''Generate alignment stats with bamtools'''
command = 'bamtools stats -in {bam} > {stats}' \
.format(bam=bam_in, stats=stats_out)
run_stage(self.state, 'bamtools_stats', command)
def fastqc(self, fastq_in, dir_out):
'''Quality check fastq file using fastqc'''
safe_make_dir(dir_out)
command = "fastqc --quiet -o {dir} {fastq}".format(dir=dir_out, fastq=fastq_in)
run_stage(self.state, 'fastqc', command)
def index_reference_samtools(self, reference_in, index_file_out):
'''Index the reference genome using samtools'''
command = 'samtools faidx {ref}'.format(ref=reference_in)
run_stage(self.state, 'index_reference_samtools', command)
def sort_bam(self, bam_in, sorted_bam_out, sorted_bam_prefix):
'''Sort the reads in a bam file using samtools'''
command = 'samtools sort {input_bam} {output_bam_prefix}' \
.format(input_bam=bam_in, output_bam_prefix=sorted_bam_prefix)
run_stage(self.state, 'sort_bam', command)
def reference_dictionary_picard(self, reference_in, dict_file_out):
'''Create a FASTA sequence dictionary for the reference using picard'''
command = 'java -jar $PICARD_HOME/lib/CreateSequenceDictionary.jar ' \
'R={ref} O={dict_file}'.format(ref=reference_in, dict_file=dict_file_out)
run_stage(self.state, 'reference_dictionary_picard', command)
def feature_finder_centroid(self, mzml_in, feature_xml_out):
'''The feature detection application for quantitation (centroided).'''
cores = self.state.config.get_stage_option('feature_finder_centroid', 'cores')
command = "FeatureFinderCentroided -threads {cores} -in {mzml_in} -out {feature_out}".format(cores=cores, mzml_in=mzml_in, feature_out=feature_xml_out)
run_stage(self.state, 'feature_finder_centroid', command)
def extract_genes_bedtools(self, bam_in, bam_out):
'''Extract MMR genes from the sorted BAM file'''
bed_file = self.state.config.get_stage_option('extract_genes_bedtools', 'bed')
command = 'bedtools intersect -abam {bam_in} -b {bed_file} > {bam_out}' \
.format(bam_in=bam_in, bed_file=bed_file, bam_out=bam_out)
run_stage(self.state, 'extract_genes_bedtools', command)
def index_reference_bowtie2(self, reference_in, index_file_out, output_prefix):
'''Index the reference genome using bowtie2'''
command = 'bowtie2-build {ref} {output_prefix}' \
.format(ref=reference_in, output_prefix=output_prefix)
run_stage(self.state, 'index_reference_bowtie2', command)
def run_java(state, stage, jar_path, mem, args):
command = java_command(jar_path, mem, args)
run_stage(state, stage, command)
def index_bam(self, bam_in, index_out):
'''Index a bam file with samtools'''
command = 'samtools index {bam}'.format(bam=bam_in)
run_stage(self.state, 'index_bam', command)
