@@ -1,65 +0,0 @@ | |||
import json | |||
import pandas as pd | |||
import sys, argparse, os | |||
parser = argparse.ArgumentParser(description="This script is to get information from multiqc") | |||
parser.add_argument('-fastqc_qualimap', '--fastqc_qualimap', type=str, help='multiqc_general_stats.txt', required=True) | |||
parser.add_argument('-fastqc', '--fastqc', type=str, help='multiqc_fastqc.txt', required=True) | |||
parser.add_argument('-fastqscreen', '--fastqscreen', type=str, help='multiqc_fastq_screen.txt', required=True) | |||
parser.add_argument('-hap', '--happy', type=str, help='multiqc_happy_data.json', required=True) | |||
args = parser.parse_args() | |||
# Rename input: | |||
fastqc_qualimap_file = args.fastqc_qualimap | |||
fastqc_file = args.fastqc | |||
fastqscreen_file = args.fastqscreen | |||
hap_file = args.happy | |||
# fastqc and qualimap | |||
dat = pd.read_table(fastqc_qualimap_file) | |||
fastqc = dat.loc[:, dat.columns.str.startswith('FastQC')] | |||
fastqc.insert(loc=0, column='Sample', value=dat['Sample']) | |||
fastqc_stat = fastqc.dropna() | |||
# qulimap | |||
qualimap = dat.loc[:, dat.columns.str.startswith('QualiMap')] | |||
qualimap.insert(loc=0, column='Sample', value=dat['Sample']) | |||
qualimap_stat = qualimap.dropna() | |||
# fastqc | |||
dat = pd.read_table(fastqc_file) | |||
fastqc_module = dat.loc[:, "per_base_sequence_quality":"kmer_content"] | |||
fastqc_module.insert(loc=0, column='Sample', value=dat['Sample']) | |||
fastqc_all = pd.merge(fastqc_stat,fastqc_module, how='outer', left_on=['Sample'], right_on = ['Sample']) | |||
# fastqscreen | |||
dat = pd.read_table(fastqscreen_file) | |||
fastqscreen = dat.loc[:, dat.columns.str.endswith('percentage')] | |||
dat['Sample'] = [i.replace('_screen','') for i in dat['Sample']] | |||
fastqscreen.insert(loc=0, column='Sample', value=dat['Sample']) | |||
# benchmark | |||
with open(hap_file) as hap_json: | |||
happy = json.load(hap_json) | |||
dat =pd.DataFrame.from_records(happy) | |||
dat = dat.loc[:, dat.columns.str.endswith('ALL')] | |||
dat_transposed = dat.T | |||
benchmark = dat_transposed.loc[:,['sample_id','METRIC.Precision','METRIC.Recall']] | |||
benchmark.columns = ['Sample','Precision','Recall'] | |||
#output | |||
fastqc_all.to_csv('fastqc.final.result.txt',sep="\t",index=0) | |||
fastqscreen.to_csv('fastqscreen.final.result.txt',sep="\t",index=0) | |||
qualimap_stat.to_csv('qualimap.final.result.txt',sep="\t",index=0) | |||
benchmark.to_csv('benchmark.final.result.txt',sep="\t",index=0) | |||
@@ -1,11 +1,12 @@ | |||
{ | |||
"{{ project_name }}.benchmarking_dir": "oss://pgx-result/renluyao/manuscript_v3.0/reference_dataset_v4.0/", | |||
"{{ project_name }}.benchmarking_dir": "oss://pgx-result/renluyao/manuscript_v3.0/reference_dataset_v202011/", | |||
"{{ project_name }}.SENTIEON_INSTALL_DIR": "/opt/sentieon-genomics", | |||
"{{ project_name }}.fasta": "GRCh38.d1.vd1.fa", | |||
"{{ project_name }}.BENCHMARKdocker": "registry-vpc.cn-shanghai.aliyuncs.com/pgx-docker-registry/rtg-hap:latest", | |||
"{{ project_name }}.gvcf": {{ gvcf_list.split(";") | tojson }}, | |||
"{{ project_name }}.gvcf_idx": {{ gvcf_idx_list.split(";") | tojson }}, | |||
"{{ project_name }}.disk_size": "500", | |||
"{{ project_name }}.del_bed": "oss://pgx-result/renluyao/manuscript_v3.0/reference_dataset_v202011/Tier1.DEL", | |||
"{{ project_name }}.project": "{{ project }}", | |||
"{{ project_name }}.SMALLcluster_config": "OnDemand bcs.ps.g.xlarge img-ubuntu-vpc", | |||
"{{ project_name }}.BIGcluster_config": "OnDemand bcs.a2.7xlarge img-ubuntu-vpc", |
@@ -34,13 +34,13 @@ task benchmark { | |||
/opt/rtg-tools/dist/rtg-tools-3.10.1-4d58ead/rtg index -f vcf ${sample}.rtg.vcf.gz | |||
if [[ ${sample} =~ "LCL5" ]];then | |||
/opt/hap.py/bin/hap.py ${benchmarking_dir}/LCL5.voted.mendelian.vcf.gz ${sample}.rtg.vcf.gz -f ${benchmarking_dir}/LCL5.highconfidence.bed --threads $nt -o ${sample} -r ${ref_dir}/${fasta} | |||
/opt/hap.py/bin/hap.py ${benchmarking_dir}/LCL5.ref.v20201103.vcf.gz ${sample}.rtg.vcf.gz -f ${benchmarking_dir}/Quartet.callable.voted.collapse.bed --threads $nt -o ${sample} -r ${ref_dir}/${fasta} | |||
elif [[ ${sample} =~ "LCL6" ]]; then | |||
/opt/hap.py/bin/hap.py ${benchmarking_dir}/LCL6.voted.mendelian.vcf.gz ${sample}.rtg.vcf.gz -f ${benchmarking_dir}/LCL6.highconfidence.bed --threads $nt -o ${sample} -r ${ref_dir}/${fasta} | |||
/opt/hap.py/bin/hap.py ${benchmarking_dir}/LCL6.ref.v20201103.vcf.gz ${sample}.rtg.vcf.gz -f ${benchmarking_dir}/Quartet.callable.voted.collapse.bed --threads $nt -o ${sample} -r ${ref_dir}/${fasta} | |||
elif [[ ${sample} =~ "LCL7" ]]; then | |||
/opt/hap.py/bin/hap.py ${benchmarking_dir}/LCL7.voted.mendelian.vcf.gz ${sample}.rtg.vcf.gz -f ${benchmarking_dir}/LCL7.highconfidence.bed --threads $nt -o ${sample} -r ${ref_dir}/${fasta} | |||
/opt/hap.py/bin/hap.py ${benchmarking_dir}/LCL7.ref.v20201103.vcf.gz ${sample}.rtg.vcf.gz -f ${benchmarking_dir}/Quartet.callable.voted.collapse.bed --threads $nt -o ${sample} -r ${ref_dir}/${fasta} | |||
elif [[ ${sample} =~ "LCL8" ]]; then | |||
/opt/hap.py/bin/hap.py ${benchmarking_dir}/LCL8.voted.mendelian.vcf.gz ${sample}.rtg.vcf.gz -f ${benchmarking_dir}/LCL8.highconfidence.bed --threads $nt -o ${sample} -r ${ref_dir}/${fasta} | |||
/opt/hap.py/bin/hap.py ${benchmarking_dir}/LCL8.ref.v20201103.vcf.gz ${sample}.rtg.vcf.gz -f ${benchmarking_dir}/Quartet.callable.voted.collapse.bed --threads $nt -o ${sample} -r ${ref_dir}/${fasta} | |||
else | |||
echo "only for quartet samples" | |||
fi |
@@ -0,0 +1,27 @@ | |||
task filtered { | |||
File raw_vcf | |||
File del_bed | |||
String family_name = basename(raw_vcf,".family.vcf") | |||
String docker | |||
String cluster_config | |||
String disk_size | |||
command <<< | |||
/opt/rtg-tools/dist/rtg-tools-3.10.1-4d58ead/rtg bgzip ${raw_vcf} -c > ${family_name}.rtg.vcf.gz | |||
/opt/rtg-tools/dist/rtg-tools-3.10.1-4d58ead/rtg index -f vcf ${family_name}.rtg.vcf.gz | |||
/opt/rtg-tools/dist/rtg-tools-3.10.1-4d58ead/rtg vcffilter -i ${family_name}.rtg.vcf.gz -o ${family_name}.noDEL.vcf.gz --exclude-bed=${del_bed} | |||
gunzip ${family_name}.noDEL.vcf.gz | |||
>>> | |||
runtime { | |||
docker:docker | |||
cluster:cluster_config | |||
systemDisk:"cloud_ssd 40" | |||
dataDisk:"cloud_ssd " + disk_size + " /cromwell_root/" | |||
} | |||
output { | |||
File noDEL_vcf="${family_name}.noDEL.vcf" | |||
} | |||
} |
@@ -1,7 +1,7 @@ | |||
task mendelian { | |||
File family_vcf | |||
File ref_dir | |||
String family_name = basename(family_vcf,".family.vcf") | |||
String family_name = basename(family_vcf,".noDEL.vcf") | |||
String fasta | |||
String docker | |||
String cluster_config |
@@ -1,6 +1,7 @@ | |||
import "./tasks/split_gvcf_files.wdl" as split_gvcf_files | |||
import "./tasks/GVCFtyper.wdl" as GVCFtyper | |||
import "./tasks/benchmark.wdl" as benchmark | |||
import "./tasks/filtered.wdl" as filtered | |||
import "./tasks/mendelian.wdl" as mendelian | |||
import "./tasks/merge_mendelian.wdl" as merge_mendelian | |||
import "./tasks/quartet_mendelian.wdl" as quartet_mendelian | |||
@@ -19,11 +20,10 @@ workflow {{ project_name }} { | |||
String SENTIEON_INSTALL_DIR | |||
String SENTIEONdocker | |||
String fasta | |||
File ref_dir | |||
File benchmarking_dir | |||
File del_bed | |||
String project | |||
@@ -96,9 +96,17 @@ workflow {{ project_name }} { | |||
Array[File] family_vcfs = merge_family.family_vcf | |||
scatter (idx in range(length(family_vcfs))) { | |||
call filtered.filtered as filtered { | |||
input: | |||
raw_vcf=family_vcfs[idx], | |||
del_bed=del_bed, | |||
docker=BENCHMARKdocker, | |||
cluster_config=BIGcluster_config, | |||
disk_size=disk_size | |||
} | |||
call mendelian.mendelian as mendelian { | |||
input: | |||
family_vcf=family_vcfs[idx], | |||
family_vcf=filtered.noDEL_vcf, | |||
ref_dir=ref_dir, | |||
fasta=fasta, | |||
docker=MENDELIANdocker, |