Version 2 (modified by 14 years ago) (diff) | ,
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Below is the current GoNL pipeline commands along with rough execution times when available on the cluster as of January 25th 2011:
This analysis pipeline consists of two parts. The first one is based on lane analysis. Afterwards lanes are merged and analysis per lane is conducted.
Lane analysis
L1. Fastq to check read quality
/tools/FastQC/fastqc /data/filename_1.fq.gz \ -Dfastqc.output_dir=/output \ -Dfastqc.unzip=false /tools/FastQC/fastqc /data/filename_2.fq.gz \ -Dfastqc.output_dir=/output \ -Dfastqc.unzip=false
L2. Align both pairs of FASTQ files using BWA (~6.5h)
/tools/bwa-0.5.8c_patched/bwa aln \ /resources//hg19/indices/b37_1kg.fa \ /data/filename_1.fq.gz -t 4 \ -f /output/filename.b37_1kg.1.sai /tools/bwa-0.5.8c_patched/bwa aln \ /resources//hg19/indices/b37_1kg.fa \ /data/filename_2.fq.gz -t 4 \ -f /output/filename.b37_1kg.2.sai
L3. Create SAM file from both .sai files using BWA sampe (~3.5h)
/tools/bwa_45_patched/bwa sampe -P -p illumina -i lane -m sample_id -l library \ /resources//hg19/indices/b37_1kg.fa \ /output/filename.b37_1kg.1.sai /output/filename.b37_1kg.2.sai \ /data/filename_1.fq.gz /data/filename_2.fq.gz \ -f /output/filename.b37_1kg.sam
L4. Convert SAM to BAM file using Picard (~0.5h)
java -jar -Xmx3g /tools/picard-tools-1.32/SamFormatConverter.jar \ INPUT=/output/filename.b37_1kg.sam \ OUTPUT=/output/filename.b37_1kg.bam \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local
L5. Sort BAM file and create corresponding index (~5h)
java -jar -Xmx3g /tools/picard-tools-1.32/SortSam.jar \ INPUT=/output/filename.b37_1kg.bam \ OUTPUT=/output/filename.b37_1kg.sorted.bam \ SORT_ORDER=coordinate \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local java -jar -Xmx3g /tools/picard-tools-1.32/BuildBamIndex.jar \ INPUT=/output/filename.b37_1kg.sorted.bam \ OUTPUT=/output/filename.b37_1kg.sorted.bam.bai \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local
L6. Calculate QC metrics on alignment using Picard (~3.5h, excluding coverage - currently not working)
This Step is currently updated as:
- Picard CalculateHsMetrics should be replaced by GATK DepthOfCoverage?
- MeanQualityByCycle and QualityScoreDistribution should be moved after the recalibration step
java -jar -Xmx4g /tools/picard-tools-1.32/CollectAlignmentSummaryMetrics.jar \ I=/output/filename.b37_1kg.sorted.bam \ O=/output/filename.b37_1kg.AlignmentSummaryMetrics \ R=/resources//hg19/indices/b37_1kg.fa \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local java -jar /tools/picard-tools-1.32/CollectGcBiasMetrics.jar \ R=/resources//hg19/indices/b37_1kg.fa \ I=/output/filename.b37_1kg.sorted.bam \ O=/output/filename.b37_1kg.GcBiasMetrics \ CHART=/output/filename.b37_1kg.GcBiasMetrics.pdf \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local java -jar /tools/picard-tools-1.32/CollectInsertSizeMetrics.jar \ I=/output/filename.b37_1kg.sorted.bam \ O=/output/filename.b37_1kg.CollectInsertSizeMetrics \ H=/output/filename.b37_1kg.CollectInsertSizeMetrics.pdf \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local java -jar /tools/picard-tools-1.32/MeanQualityByCycle.jar \ I=/output/filename.b37_1kg.sorted.bam \ O=/output/filename.b37_1kg.MeanQualityByCycle \ CHART=/output/filename.b37_1kg.MeanQualityByCycle.pdf \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local java -jar /tools/picard-tools-1.32/QualityScoreDistribution.jar \ I=/output/filename.b37_1kg.sorted.bam \ O=/output/filename.b37_1kg.[wiki:QualityScoreDistribution] \ CHART=/output/filename.b37_1kg.[wiki:QualityScoreDistribution].pdf \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local java -jar /tools/picard-tools-1.32/BamIndexStats.jar \ INPUT=/output/filename.b37_1kg.sorted.bam \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local java -jar -Xmx3g /tools/picard-tools-1.32/CalculateHsMetricsWholeGenome.jar \ INPUT=/output/filename.b37_1kg.sorted.bam \ OUTPUT=/output/filename.b37_1kg.HsMetrics \ BAIT_INTERVALS=/resources//hg19/intervals/GoNL.interval_list \ TARGET_INTERVALS=/resources//hg19/intervals/GoNL.interval_list \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local
L7. Mark duplicates after alignment (~2.5h)
java -Xmx4g -jar /tools/picard-tools-1.32/MarkDuplicates.jar \ INPUT=/output/filename.b37_1kg.sorted.bam \ OUTPUT=/output/filename.b37_1kg.dedup.bam \ METRICS_FILE=/output/filename.b37_1kg.dedup.metrics \ REMOVE_DUPLICATES=false ASSUME_SORTED=true VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local
L8. Realignment using knowns only (~2.5h)
java -Djava.io.tmpdir=/local -Xmx8g -jar \ /tools/Sting/dist/GenomeAnalysisTK.jar -l INFO -T IndelRealigner \ -U ALLOW_UNINDEXED_BAM -I /output/filename.b37_1kg.dedup.bam \ -targetIntervals /resources//hg19/intervals/realign_intervals_hg19_b37_1kg.intervals \ -R /resources//hg19/indices/b37_1kg.fa \ -D /resources//hg19/dbsnp/dbsnp_129_b37_b37_1kg.rod \ -[B:indels,VCF B:indels,VCF] /resources//hg19/indels/1kg.pilot_release.merged.indels.sites./hg19.b37_1kg.vcf \ -o /output/filename.b37_1kg.realigned.bam -knownsOnly -LOD 0.4 -compress 0
L9. Fix mates after realignment (~2h)
java -jar -Xmx6g /tools/picard-tools-1.32/FixMateInformation.jar \ INPUT=/output/filename.b37_1kg.realigned.bam \ OUTPUT=/output/filename.b37_1kg.matefixed.bam \ SORT_ORDER=coordinate VALIDATION_STRINGENCY=SILENT TMP_DIR=/local
L10. Calculate covariates before realignment (~12h - Note that this should be improved using more cores. In test at the moment)
java -jar -Xmx2g /tools/Sting/dist/GenomeAnalysisTK.jar -l INFO \ -T CountCovariates -U ALLOW_UNINDEXED_BAM \ -R /resources//hg19/indices/b37_1kg.fa \ --DBSNP /resources//hg19/dbsnp/dbsnp_129_b37_b37_1kg.rod \ -I /output/filename.b37_1kg.matefixed.bam \ -cov ReadGroupcovariate -cov QualityScoreCovariate -cov CycleCovariate -cov DinucCovariate \ -recalFile /output/filename.b37_1kg.matefixed.covariate_table.csv
L11. Recalibrate mate fixed and realigned alignment (~5h)
java -jar -Xmx4g /tools/Sting/dist/GenomeAnalysisTK.jar -l INFO \ -T TableRecalibration -U ALLOW_UNINDEXED_BAM \ -R /resources//hg19/indices/b37_1kg.fa -I /output/filename.b37_1kg.matefixed.bam \ --recal_file /output/filename.b37_1kg.matefixed.covariate_table.csv \ --out /output/filename.b37_1kg.recal.bam
L12. Sort and index recalibrated alignment (~5h)
java -jar -Xmx3g /tools/picard-tools-1.32/SortSam.jar \ INPUT=/output/filename.b37_1kg.recal.bam \ OUTPUT=/output/filename.b37_1kg.recal.sorted.bam \ SORT_ORDER=coordinate \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local java -jar -Xmx3g /tools/picard-tools-1.32/BuildBamIndex.jar \ INPUT=/output/filename.b37_1kg.recal.sorted.bam \ OUTPUT=/output/filename.b37_1kg.recal.sorted.bam.bai \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local
L13. Calculate covariates after realignment and recalibration (~12h Note that this should be improved using more cores. In test at the moment)
java -jar -Xmx2g /tools/Sting/dist/GenomeAnalysisTK.jar -l INFO \ -T CountCovariates -U ALLOW_UNINDEXED_BAM \ -R /resources//hg19/indices/b37_1kg.fa \ --DBSNP /resources//hg19/dbsnp/dbsnp_129_b37_b37_1kg.rod \ -I /output/filename.b37_1kg.recal.sorted.bam \ -cov ReadGroupcovariate -cov QualityScoreCovariate -cov CycleCovariate -cov DinucCovariate \ -recalFile /output/filename.b37_1kg.recal.covariate_table.csv
L14. Analyze covariates before and after (Currently not working)
java -jar -Xmx4g /tools/Sting/dist/AnalyzeCovariates.jar -l INFO \ -resources /resources//hg19/indices/b37_1kg.fa \ --recal_file /output/filename.b37_1kg.matefixed.covariate_table.csv \ -outputDir /output/filename.b37_1kg.recal.stats_before/ \ -Rscript ${rscript} -ignoreQ 5 java -jar -Xmx4g /tools/Sting/dist/AnalyzeCovariates.jar -l INFO \ -resources /resources//hg19/indices/b37_1kg.fa \ --recal_file /output/filename.b37_1kg.recal.covariate_table.csv \ -outputDir /output/filename.b37_1kg.recal.stats_after/ \ -Rscript ${rscript} -ignoreQ 5
Sample analysis
S1. Merging three lanes to one
java -jar -Xmx4g /tools/picard-tools-1.32/MergeSamFiles.jar \ INPUT/output/filename.b37_1kg.recal.sorted.ba \ INPUT/output/filename2.b37_1kg.recal.sorted.ba \ INPUT/output/filename3.b37_1kg.recal.sorted.ba \ ASSUME_SORTED=true USE_THREADING=true \ TMP_DIR=/local MAX_RECORDS_IN_RAM=30000000 \ OUTPUT=/output/sample_id.b37_1kg.bam SORT_ORDER=coordinate \ VALIDATION_STRINGENCY=SILENT
To perform QC on initial data SNP calling is performed. This procedure consists of three steps.
S2. SNP calling using Unified Genotyper
java -Xmx4g -jar /tools/Sting/dist/GenomeAnalysisTK.jar \ -l INFO -T UnifiedGenotyper -I /output/sample_id.b37_1kg.bam \ --out /output/sample_id.b37_1kg.qc_check_snps.vcf \ -R /resources//hg19/indices/b37_1kg.fa \ -D /resources//hg19/dbsnp/dbsnp_129_b37_b37_1kg.rod \ -stand_call_conf 30.0 -stand_emit_conf 10.0
S3. Filter SNPs using variant filtration
java -jar -Xmx4g /tools/Sting/dist/GenomeAnalysisTK.jar \ -l INFO -T VariantFiltration \ -[B:variant,VCF B:variant,VCF] /output/sample_id.b37_1kg.qc_check_snps.vcf \ -R /resources//hg19/indices/b37_1kg.fa \ -D /resources//hg19/dbsnp/dbsnp_129_b37_b37_1kg.rod \ --out /output/sample_id.b37_1kg.qc_check_snps.filtered.vcf \ --maskName InDel --clusterWindowSize 10 \ --filterName GATK_standard \ --filterExpression "AB > 0.75 && DP > 40 || DP > 100 || MQ0 > 40 || SB > -0.10"||
S4. Generate statistics on called SNPs using variant eval
java -Xmx4g -jar /tools/Sting/dist/GenomeAnalysisTK.jar \ -T VariantEval -R /resources//hg19/indices/b37_1kg.fa \ -l INFO \ -[B:eval,VCF B:eval,VCF] /output/sample_id.b37_1kg.qc_check_snps.filtered.vcf \ -D /resources//hg19/dbsnp/dbsnp_129_b37_b37_1kg.rod \ -o /output/sample_id.b37_1kg.qc_check_snps.filtered.eval
After this QC check the indel and SNP calling takes place using the next commands.
S5. Create targets for realignment
java -Xmx4g -jar -Djava.io.tmpdir=/local /tools/Sting/dist/GenomeAnalysisTK.jar -l INFO \ -T RealignerTargetCreator \ -I /output/sample_id.b37_1kg.bam \ -R /resources//hg19/indices/b37_1kg.fa \ -D /resources//hg19/dbsnp/dbsnp_129_b37_b37_1kg.rod \ -[B:indels,VCF B:indels,VCF] /resources//hg19/indels/1kg.pilot_release.merged.indels.sites./hg19.b37_1kg.vcf \ -o /output/sample_id.b37_1kg.realign.intervals
S6. Realignment using created targets, dbSNP and indels from 1kg project
java -Djava.io.tmpdir=/local –Xmx6g -jar \ /tools/Sting/dist/GenomeAnalysisTK.jar -l INFO -T IndelRealigner \ -I /output/sample_id.b37_1kg.bam \ -targetIntervals /output/sample_id.b37_1kg.realign.intervals \ -R /resources//hg19/indices/b37_1kg.fa \ -D /resources//hg19/dbsnp/dbsnp_129_b37_b37_1kg.rod \ -[B:indels,VCF B:indels,VCF] /resources//hg19/indels/1kg.pilot_release.merged.indels.sites./hg19.b37_1kg.vcf \ --out /output/sample_id.b37_1kg.realigned.bam \ -maxReads 500000
S7. Fix mates after realignment and create corresponding BAM index
java -jar -Xmx6g /tools/picard-tools-1.32/FixMateInformation.jar \ INPUT=/output/sample_id.b37_1kg.realigned.bam \ OUTPUT=/output/sample_id.b37_1kg.matesfixed.bam \ SORT_ORDER=coordinate VALIDATION_STRINGENCY=SILENT TMP_DIR=/local java -jar -Xmx3g /tools/picard-tools-1.32/BuildBamIndex.jar \ INPUT=/output/sample_id.b37_1kg.matesfixed.bam \ OUTPUT=/output/sample_id.b37_1kg.matesfixed.bam.bai \ VALIDATION_STRINGENCY=LENIENT \ TMP_DIR=/local
S8. Indel calling on realigned BAM file
java -Xmx4g -jar /tools/Sting/dist/GenomeAnalysisTK.jar -l INFO \ -T IndelGenotyperV2 -I /output/sample_id.b37_1kg.matesfixed.bam \ --out /output/sample_id.b37_1kg.indels.vcf \ --bedOutput /output/sample_id.b37_1kg.indels.bed \ -R /resources//hg19/indices/b37_1kg.fa \ -verbose /output/sample_id.b37_1kg.indels.verboseoutput.txt
S9. Filter indels
perl /tools/filterSingleSampleCalls.pl \ --calls /output/sample_id.b37_1kg.indels.bed > /output/sample_id.b37_1kg.indels.filtered.bed \ --max_cons_av_mm 3.0 --max_cons_nqs_av_mm 0.5 --mode ANNOTATE
S10. SNP calling on realigned BAM file
java -Xmx4g -jar /tools/Sting/dist/GenomeAnalysisTK.jar \ -l INFO -T UnifiedGenotyper -I /output/sample_id.b37_1kg.matesfixed.bam \ --out /output/sample_id.b37_1kg.snps.vcf \ -R /resources//hg19/indices/b37_1kg.fa \ -D /resources//hg19/dbsnp/dbsnp_129_b37_b37_1kg.rod \ -stand_call_conf 30.0 -stand_emit_conf 10.0
S11. Create indel mask used in SNP calling python
/tools/makeIndelMask.py \ /output/sample_id.b37_1kg.indels.filtered.bed 10 \ /output/sample_id.b37_1kg.indels.mask.bed
S12. Filter SNP calls using the indel mask, dbsnp and indels from 1kg project
java -jar -Xmx4g /tools/Sting/dist/GenomeAnalysisTK.jar \ -l INFO -T VariantFiltration \ -[B:variant,VCF B:variant,VCF] /output/sample_id.b37_1kg.snps.vcf \ -[B:mask,Bed B:mask,Bed] /output/sample_id.b37_1kg.indels.mask.bed \ -R /resources//hg19/indices/b37_1kg.fa \ -D /resources//hg19/dbsnp/dbsnp_129_b37_b37_1kg.rod \ --out /output/sample_id.b37_1kg.snps.filtered.vcf \ --maskName InDel --clusterWindowSize 10 \ --filterName GATK_standard \ --filterExpression "AB > 0.75 && DP > 40 || DP > 100 || MQ0 > 40 || SB > -0.10"||
S13. Variant eval on detected SNPs
java -Xmx4g -jar /tools/Sting/dist/GenomeAnalysisTK.jar \ -T VariantEval -R /resources//hg19/indices/b37_1kg.fa \ -l INFO \ -[B:eval,VCF B:eval,VCF] /output/sample_id.b37_1kg.snps.filtered.vcf \ -D /resources//hg19/dbsnp/dbsnp_129_b37_b37_1kg.rod \ -o /output/sample_id.b37_1kg.snps.filtered.eval