merge sentieon

codescripts/extract_tables.py

+import json
+import pandas as pd
+import sys, argparse, os
+
+parser = argparse.ArgumentParser(description="This script is to get information from multiqc and sentieon, output the raw fastq, bam and variants calling (precision and recall) quality metrics")
+
+
+parser.add_argument('-quality', '--quality_yield', type=str, help='*.quality_yield.txt',  required=True)
+parser.add_argument('-depth', '--wgs_metrics', type=str, help='*deduped_WgsMetricsAlgo.txt',  required=True)
+parser.add_argument('-aln', '--aln_metrics', type=str, help='*_deduped_aln_metrics.txt',  required=True)
+parser.add_argument('-is', '--is_metrics', type=str, help='*_deduped_is_metrics.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:
+quality_yield_file = args.quality_yield
+wgs_metrics_file = args.wgs_metrics
+aln_metrics_file = args.aln_metrics
+is_metrics_file = args.is_metrics
+
+fastqc_file = args.fastqc
+fastqscreen_file = args.fastqscreen
+hap_file = args.happy
+
+#############################################
+# fastqc
+fastqc = pd.read_table(fastqc_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'])
+
+# pre-alignment
+pre_alignment_dat = pd.merge(fastqc,fastqscreen,how="outer",left_on=['Sample'],right_on=['Sample'])
+pre_alignment_dat['FastQC_mqc-generalstats-fastqc-total_sequences'] = pre_alignment_dat['FastQC_mqc-generalstats-fastqc-total_sequences']/1000000
+del pre_alignment_dat['FastQC_mqc-generalstats-fastqc-percent_fails']
+del pre_alignment_dat['FastQC_mqc-generalstats-fastqc-avg_sequence_length']
+del pre_alignment_dat['ERCC percentage']
+del pre_alignment_dat['Phix percentage']
+del pre_alignment_dat['Mouse percentage']
+pre_alignment_dat = pre_alignment_dat.round(2)
+pre_alignment_dat.columns = ['Sample','%Dup','%GC','Total Sequences (million)','%Human','%EColi','%Adapter','%Vector','%rRNA','%Virus','%Yeast','%Mitoch','%No hits']
+pre_alignment_dat.to_csv('pre_alignment.txt',sep="\t",index=0)
+
+
+
+############################
+dat = pd.read_table(aln_metrics_file)
+dat['PCT_ALIGNED_READS'] = dat["PF_READS_ALIGNED"]/dat["TOTAL_READS"]
+aln_metrics = dat[["Sample", "PCT_ALIGNED_READS","PF_MISMATCH_RATE"]]
+aln_metrics = aln_metrics * 100
+
+dat = pd.read_table(is_metrics_file)
+is_metrics = dat[['Sample', 'MEDIAN_INSERT_SIZE']]
+
+dat = pd.read_table(quality_yield_file)
+dat['%Q20'] = dat['Q20_BASES']/dat['TOTAL_BASES']
+dat['%Q30'] = dat['Q30_BASES']/dat['TOTAL_BASES']
+quality_yield = dat[['Sample','%Q20','%Q30']]
+quality_yield = quality_yield * 100
+
+dat = pd.read_table(wgs_metrics_file)
+wgs_metrics = dat[['Sample','MEDIAN_COVERAGE','PCT_1X', 'PCT_5X', 'PCT_10X','PCT_30X']]
+wgs_metrics['PCT_1X'] = wgs_metrics['PCT_1X'] * 100
+wgs_metrics['PCT_5X'] = wgs_metrics['PCT_5X'] * 100
+wgs_metrics['PCT_10X'] = wgs_metrics['PCT_10X'] * 100
+wgs_metrics['PCT_30X'] = wgs_metrics['PCT_30X'] * 100
+
+data_frames = [aln_metrics, is_metrics, quality_yield, wgs_metrics]
+post_alignment_dat = reduce(lambda  left,right: pd.merge(left,right,on=['Sample'],how='outer'), data_frames)
+
+# 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)
+
+
+
+
+
+

tasks/extract_tables.wdl

 task extract_tables {
 
+	File quality_yield_summary
+	File wgs_metrics_summary
+	File aln_metrics_summary
+	File is_metrics_summary
+
 	File fastqc
 	File fastqscreen
 	File hap
-	File aln
-	File quality_yield
-	File wgs_metrics
 
 	String docker
 	String cluster_config
 	String disk_size
 
 	command <<<
-		python /opt/extract_multiqc.py -fastqc_qualimap ${fastqc} -fastqc ${fastqc} -fastqscreen ${fastqscreen} -hap ${hap}
+
+
+
 	>>>
 
 	runtime {

tasks/mergeSentieon.wdl

-task mergeSentieon {
-	Array[File] aln_metrics_header
-	Array[File] aln_metrics_data
-
-	Array[File] is_metrics_header
-	Array[File] is_metrics_data
-
-	Array[File] quality_yield_header
-	Array[File] quality_yield_data
-
-	Array[File] wgs_metrics_header
-	Array[File] wgs_metrics_data
-
-	String docker
-	String cluster_config
-	String disk_size
-
-	command <<<
-		set -o pipefail
-		set -e
-		echo '''Sample''' > sample_column
-		cat ${sep=" " aln_metrics_header} | sed -n '1,1p' | cat - ${sep=" " aln_metrics_data} > aln_metrics
-		ls ${sep=" " aln_metrics_data} | cut -d '.' -f1 | cat sample_column - | paste - aln_metrics > aln_metrics.txt
-		cat ${sep=" " is_metrics_header} | sed -n '1,1p' | cat - ${sep=" " is_metrics_data} > is_metrics.txt
-		
-		cat ${sep=" " quality_yield_header} | sed -n '1,1p' | cat - ${sep=" " quality_yield_data} > quality_yield_data.txt
-		cat ${sep=" " wgs_metrics_header} | sed -n '1,1p' | cat - ${sep=" " wgs_metrics_data} > wgs_metrics_data.txt		
-	>>>
-
-	runtime {
-		docker:docker
-		cluster:cluster_config
-		systemDisk:"cloud_ssd 40"
-		dataDisk:"cloud_ssd " + disk_size + " /cromwell_root/"
-	}
-
-	output {
-		File aln_metrics_merge = "aln_metrics.txt"
-		File is_metrics_merge = "is_metrics.txt"
-		File quality_yield_merge = "quality_yield_data.txt"
-		File wgs_metrics_merge = "wgs_metrics_data.txt"
-	}
-}

tasks/merge_family.wdl

- task merge_family {
+task merge_family {
 	Array[File] splited_vcf
 	String project
 	String docker

tasks/merge_sentieon_metrics.wdl

+task merge_sentieon_metrics {
+	Array[File] quality_yield_header
+	Array[File] wgs_metrics_algo_header
+	Array[File] aln_metrics_header
+	Array[File] is_metrics_header
+
+	Array[File] quality_yield_data
+	Array[File] wgs_metrics_algo_data
+	Array[File] aln_metrics_data
+	Array[File] is_metrics_data
+
+	String project
+	String docker
+	String cluster_config
+	String disk_size
+	
+	command <<<
+		echo '''Sample''' > sample_column
+
+		cat ${sep=" " quality_yield_header} | sed -n '1,1p' | cat - ${sep=" " quality_yield_data} > quality_yield_all
+		ls ${sep=" " quality_yield_data} | cut -d '.' -f1 | cat sample_column - | paste - quality_yield_all > ${project}.quality_yield.txt
+
+		cat ${sep=" " wgs_metrics_algo_header} | sed -n '1,1p' | cat - ${sep=" " wgs_metrics_algo_data} > wgs_metrics_all	
+		ls ${sep=" " wgs_metrics_algo_data} | cut -d '.' -f1 | cat sample_column - | paste - wgs_metrics_all > ${project}.wgs_metrics_data.txt
+		
+		cat ${sep=" " aln_metrics_header} | sed -n '1,1p' | cat - ${sep=" " aln_metrics_data} > aln_metrics_all
+		ls ${sep=" " aln_metrics_data} | cut -d '.' -f1 | cat sample_column - | paste - aln_metrics_all > ${project}.aln_metrics.txt
+
+
+		cat ${sep=" " is_metrics_header} | sed -n '1,1p' | cat - ${sep=" " is_metrics_data} > is_metrics_all
+		ls ${sep=" " is_metrics_data} | cut -d '.' -f1 | cat sample_column - | paste - is_metrics_all > ${project}.is_metrics.txt
+
+	>>>
+
+	runtime {
+		docker:docker
+		cluster: cluster_config
+		systemDisk: "cloud_ssd 40"
+		dataDisk: "cloud_ssd " + disk_size + " /cromwell_root/"
+	}
+
+	output {
+		File quality_yield_summary = "${project}.quality_yield.txt"
+		File wgs_metrics_summary = "${project}.wgs_metrics_data.txt"
+		File aln_metrics_summary = "${project}.aln_metrics.txt"
+		File is_metrics_summary = "${project}.is_metrics.txt"
+	}
+}

tasks/sentieon.wdl

 task sentieon {
+	File quality_yield
+	File wgs_metrics_algo
 	File aln_metrics
 	File is_metrics
-	File wgsmetrics
-	File quality_yield
+
+	String sample
 	String docker
 	String cluster_config
 	String disk_size
 	command <<<
 		set -o pipefail
 		set -e
+
+		cat ${quality_yield} | sed -n '2,2p' > quality_yield.header
+		cat ${quality_yield} | sed -n '3,3p' > ${sample}.quality_yield
+
+		cat ${wgs_metrics_algo} | sed -n '2,2p' > wgs_metrics_algo.header
+		cat ${wgs_metrics_algo} | sed -n '3,3p' > ${sample}.wgs_metrics_algo
+
 		cat ${aln_metrics} | sed -n '2,2p'  > aln_metrics.header
-		cat ${aln_metrics} | sed -n '5,5p'  > ${sample_name}.aln_metrics
-		cat ${dedup_metrics} | sed -n '2,2p' > dedup_metrics.header
-		cat ${dedup_metrics} | sed -n '3,3p' > ${sample_name}.dedup_metrics
+		cat ${aln_metrics} | sed -n '5,5p'  > ${sample}.aln_metrics
+
 		cat ${is_metrics} | sed -n '2,2p' > is_metrics.header
-		cat ${is_metrics} | sed -n '3,3p' > ${sample_name}.is_metrics
-		cat ${deduped_coverage} | sed -n '1,1p' > deduped_coverage.header
-		cat ${deduped_coverage} | sed -n '2,2p' > ${sample_name}.deduped_coverage
+		cat ${is_metrics} | sed -n '3,3p' > ${sample}.is_metrics
+
 	>>>
 
 	runtime {
 	}
 
 	output {
+		File quality_yield_header = "quality_yield.header"
+		File quality_yield_data = "${sample}.quality_yield"
+		File wgs_metrics_algo_header = "wgs_metrics_algo.header"
+		File wgs_metrics_algo_data = "${sample}.wgs_metrics_algo"
 		File aln_metrics_header = "aln_metrics.header"
-		File aln_metrics_data = "${sample_name}.aln_metrics"
-		File dedup_metrics_header = "dedup_metrics.header"
-		File dedup_metrics_data = "${sample_name}.dedup_metrics"
+		File aln_metrics_data = "${sample}.aln_metrics"
 		File is_metrics_header = "is_metrics.header"
-		File is_metrics_data = "${sample_name}.is_metrics"
-		File deduped_coverage_header = "deduped_coverage.header"
-		File deduped_coverage_data = "${sample_name}.deduped_coverage"
+		File is_metrics_data = "${sample}.is_metrics"
 	}
 }

workflow.wdl

 import "./tasks/mapping.wdl" as mapping
 import "./tasks/Dedup.wdl" as Dedup
 import "./tasks/deduped_Metrics.wdl" as deduped_Metrics
+import "./tasks/sentieon.wdl" as sentieon
 import "./tasks/Realigner.wdl" as Realigner
 import "./tasks/BQSR.wdl" as BQSR
 import "./tasks/Haplotyper_gVCF.wdl" as Haplotyper_gVCF
 import "./tasks/split_gvcf_files.wdl" as split_gvcf_files
 import "./tasks/benchmark.wdl" as benchmark
 import "./tasks/multiqc.wdl" as multiqc
+import "./tasks/merge_sentieon_metrics.wdl" as merge_sentieon_metrics
 import "./tasks/mendelian.wdl" as mendelian
 import "./tasks/merge_mendelian.wdl" as merge_mendelian
 import "./tasks/quartet_mendelian.wdl" as quartet_mendelian
 			disk_size=disk_size,
 			cluster_config=BIGcluster_config
 		}
+
+		call sentieon.sentieon as sentieon {
+			input:
+			quality_yield=deduped_Metrics.deduped_QualityYield,
+			wgs_metrics_algo=deduped_Metrics.deduped_wgsmetrics,
+			aln_metrics=deduped_Metrics.dedeuped_aln_metrics,
+			is_metrics=deduped_Metrics.deduped_is_metrics,
+			sample=quartet[2],
+			docker=SENTIEONdocker,
+			cluster_config=SMALLcluster_config,
+			disk_size=disk_size		
+		}
+
 		call Realigner.Realigner as Realigner {
 			input:
 			SENTIEON_INSTALL_DIR=SENTIEON_INSTALL_DIR,
 		disk_size=disk_size
 	}
 
+	call merge_sentieon_metrics.merge_sentieon_metrics as merge_sentieon_metrics {
+		input:
+		quality_yield_header=sentieon.quality_yield_header,
+		wgs_metrics_algo_header=sentieon.wgs_metrics_algo_header,
+		aln_metrics_header=sentieon.aln_metrics_header,
+		is_metrics_header=sentieon.is_metrics_header,
+		quality_yield_data=sentieon.quality_yield_data,
+		wgs_metrics_algo_data=sentieon.wgs_metrics_algo_data,
+		aln_metrics_data=sentieon.aln_metrics_data,
+		is_metrics_data=sentieon.is_metrics_data,
+		project=project,
+		docker=MULTIQCdocker,
+		cluster_config=SMALLcluster_config,
+		disk_size=disk_size	
+	}
+
 	call extract_tables.extract_tables as extract_tables {
 		input:
+		quality_yield_summary=merge_sentieon_metrics.quality_yield_summary,
+		wgs_metrics_summary=merge_sentieon_metrics.wgs_metrics_summary,
+		aln_metrics_summary=merge_sentieon_metrics.aln_metrics_summary,
+		is_metrics_summary=merge_sentieon_metrics.is_metrics_summary,
 		fastqc=multiqc.fastqc,
 		fastqscreen=multiqc.fastqscreen,
 		hap=multiqc.hap,
-		aln=deduped_Metrics.dedeuped_aln_metrics,
-		quality_yield=deduped_Metrics.deduped_QualityYield,
-		wgs_metrics=deduped_Metrics.deduped_wgsmetrics,
-		docker=DIYdocker,
+		docker=MULTIQCdocker,
 		cluster_config=SMALLcluster_config,
 		disk_size=disk_size
-	}
+	}	
 
 	Boolean sister_tag = read_boolean(split_gvcf_files.sister_tag)
 	Boolean quartet_tag = read_boolean(split_gvcf_files.quartet_tag)