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VQSR tag in FILTER is false positive variant ?
Sunhye
KoreaMember ✭
Hi.
I wonder whether after VQSR , the variants which have VQSR tag in FILTER column filter out, including VQSRTrancheINDEL99.00 to 99.90, VQSRTrancheINDEL99.90 to 100.00+, VQSRTrancheINDEL99.90 to 100.00, VQSRTrancheSNP99.90 to 100.00, VQSRTrancheSNP99.90 to 100.00+? These means are false positive variants?
and What do 100.00+ mean?
Can I have Only "PASS" variants tin FILTER tab as true positve variant ?
Tagged:
Answers
@Sunhye
Hi,
Can you tell me what version of GATK you are using and the exact commands you ran in the VQSR step?
Also, please post some example records from your output VCF.
Thanks,
Sheila
Hi @Sheila !
My GATK version is 3.4-46-gbc02625.
My commands is,
#VQSR java -Xmx64g -jar ${GATK} -R ${REF} -T VariantRecalibrator -input project.raw.joint.chr${chr}.vcf \ -recalFile project.joint.chr${chr}.recalibrate_SNP.recal \ -tranchesFile project.joint.chr${chr}.recalibrate_SNP.tranches \ -rscriptFile project.chr${chr}.recalibrate_SNP_plots.R -nt 32 -L ${chr} \ -resource:hapmap,known=false,training=true,truth=true,prior=15.0 ${bundle}/hapmap_3.3.b37.vcf \ -resource:omni,known=false,training=true,truth=true,prior=12.0 ${bundle}/1000G_omni2.5.b37.vcf \ -resource:1000G,known=false,training=true,truth=false,prior=10.0 ${bundle}/1000G_phase1.snps.high_confidence.b37.vcf \ -resource:dbsnp,known=true,training=false,truth=false,prior=2.0 ${bundle}/dbsnp_138.b37.vcf \ -an QD -an MQ -an MQRankSum -an ReadPosRankSum -an FS -an SOR -an DP -an InbreedingCoeff -mode SNP \ --log_to_file chr${chr}.vqsr.snp.log java -Xmx64g -jar ${GATK} -R ${REF} -T ApplyRecalibration \ -input project.raw.joint.chr${chr}.vcf -mode SNP --ts_filter_level 99.5 \ -recalFile project.joint.chr${chr}.recalibrate_SNP.recal -tranchesFile project.joint.chr${chr}.recalibrate_SNP.tranches \ -o project.joint.raw.chr${chr}.recalibrated_snps.vcf -nt 32 --log_to_file chr${chr}.apply.recal.snp.log java -Xmx64g -jar ${GATK} -R ${REF} -T VariantRecalibrator \ -input project.joint.raw.chr${chr}.recalibrated_snps.vcf -recalFile project.joint.chr${chr}.recalibrate_INDEL.recal \ -tranchesFile project.joint.chr${chr}.recalibrate_INDEL.tranches -rscriptFile project.chr${chr}.recalibrate_INDEL_plots.R -nt 32 \ --maxGaussians 4 -L ${chr} \ -resource:mills,known=true,training=true,truth=true,prior=12.0 ${bundle}/Mills_and_1000G_gold_standard.indels.b37.vcf \ -resource:dbsnp,known=true,training=false,truth=false,prior=2.0 ${bundle}/dbsnp_138.b37.vcf \ -an QD -an DP -an FS -an SOR -an ReadPosRankSum -an MQRankSum -an InbreedingCoeff -mode INDEL \ --log_to_file vqsr.indel.log java -Xmx64g -jar ${GATK} -R ${REF} -T ApplyRecalibration \ -input project.joint.raw.chr${chr}.recalibrated_snps.vcf -mode INDEL --ts_filter_level 99.0 \ -recalFile project.joint.chr${chr}.recalibrate_INDEL.recal -tranchesFile project.joint.chr${chr}.recalibrate_INDEL.tranches -nt 32 \ -o project.joint.chr${chr}.recalibrated_snps.indel.vcf --log_to_file chr${chr}.apply.recal.indel.logFinally, vcf recode is,
@Sunhye
Hi,
Those VQSLOD score do not look good. Can you post the tranche plots and recalibration plots?
Thanks,
Sheila
Hi @Sheila
I'm so sorry my late reply.
For chr4.recal.vcf, I attach files about the tranche plots and recalibration plots.
Could you check these files?
And I wonder that about variant filtering, VQS LOD value should use than than the presence or absence of the VQSR tag in filter colum to filter variant?
If so, what is VQS LOD's range to decide filtering ?
@Sunhye
Hi,
Sorry for the late response. Can you tell me more about your samples and how you ran VQSR? How many samples do you have and are they whole genome or whole exome?
Thanks,
Sheila
@Sunhye I'm not sure I will be of much help, but here goes. I noticed this part of your command:
-input project.joint.raw.chr${chr}.recalibrated_snps.vcfPreferably you should run VR across all chromosomes simultaneously/concurrently.
You should filter on truth sensitivity tranches; not on VQSLOD values.
It is described in your VCF header, which VQSLOD values this corresponds to:
It depends what TS threshold you use, when you run ApplyRecalibration.
Hi @Sheila .
My samples are 62 individuals and whole genome sequencing.
And How to run VQSR is followed by GATK best practice.
For SNP,
java -Xmx64g -jar ${GATK} -R ${REF} -T VariantRecalibrator -input project.raw.joint.chr${chr}.vcf \ -recalFile project.joint.chr${chr}.recalibrate_SNP.recal \ -tranchesFile project.joint.chr${chr}.recalibrate_SNP.tranches \ -rscriptFile project.chr${chr}.recalibrate_SNP_plots.R -nt 32 -L ${chr} \ -resource:hapmap,known=false,training=true,truth=true,prior=15.0 ${bundle}/hapmap_3.3.b37.vcf \ -resource:omni,known=false,training=true,truth=true,prior=12.0 ${bundle}/1000G_omni2.5.b37.vcf \ -resource:1000G,known=false,training=true,truth=false,prior=10.0 ${bundle}/1000G_phase1.snps.high_confidence.b37.vcf \ -resource:dbsnp,known=true,training=false,truth=false,prior=2.0 ${bundle}/dbsnp_138.b37.vcf \ -an QD -an MQ -an MQRankSum -an ReadPosRankSum -an FS -an SOR -an DP -an InbreedingCoeff -mode SNP \For Indel,
java -Xmx64g -jar ${GATK} -R ${REF} -T VariantRecalibrator \ -input project.joint.raw.chr${chr}.recalibrated_snps.vcf -recalFile project.joint.chr${chr}.recalibrate_INDEL.recal \ -tranchesFile project.joint.chr${chr}.recalibrate_INDEL.tranches -rscriptFile project.chr${chr}.recalibrate_INDEL_plots.R -nt 32 \ --maxGaussians 4 -L ${chr} \ -resource:mills,known=true,training=true,truth=true,prior=12.0 ${bundle}/Mills_and_1000G_gold_standard.indels.b37.vcf \ -resource:dbsnp,known=true,training=false,truth=false,prior=2.0 ${bundle}/dbsnp_138.b37.vcf \ -an QD -an DP -an FS -an SOR -an ReadPosRankSum -an MQRankSum -an InbreedingCoeff -mode INDEL \ --log_to_file vqsr.indel.logHi @tommycarstensen !
Thanks for your detailed comment!
Your reply are very helpful to me!