I have exome sequencing with 69 human samples and used the GATK pipeline with joint calling. But got too many variant calls after the joint calling (~2 million calls per subject) before filtering. even if after the filtering using VQSR and GQ > 20, I still have ~500 k of variant calls. anything wrong in my pipeline?
below is my pipeline:
1 answer
--emitRefConfidence GVCF
You're creating a GVCF, that is not a VCF (https://gatkforums.broadinstitute.org/gatk/discussion/4017/), you need to call GenotypeGVFs
I actually perform joint calling:
gatk -T GenotypeGVCFs -R ucsc.hg19.fasta -V raw_variant.0107-2-1.g.vcf -V raw_variant.0107-2-A.g.vcf -V raw_variant.0107-2-B.g.vcf ...
and then
##### Recalibrate variant quality scores = run VQSR
### 1. Prepare recalibration parameters for SNPs
### 2. Build the SNP recalibration model
gatk -T VariantRecalibrator -R ucsc.hg19.fasta -input variant_raw_joint.vcf -resource:hapmap,known=false,training=true,truth=true,prior=15.0 hapmap_3.3.hg19.sites.vcf -resource:omni,known=false,training=true,truth=true,prior=12.0 1000G_omni2.5.hg19.sites.vcf -resource:1000G,known=false,training=true,truth=false,prior=10.0 1000G_phase1.snps.high_confidence.hg19.sites.vcf -resource:dbsnp,known=true,training=false,truth=false,prior=2.0 dbsnp_138.hg19.vcf -an QD -an FS -an SOR -an MQ -an MQRankSum -an ReadPosRankSum -an InbreedingCoeff -mode SNP -tranche 100.0 -tranche 99.9 -tranche 99.0 -tranche 90.0 -recalFile recalibrate_SNP.recal -tranchesFile recalibrate_SNP.tranches -rscriptFile recalibrate_SNP_plots.R
### 3. Apply the desired level of recalibration to the SNPs in the call set
gatk -T ApplyRecalibration -R ucsc.hg19.fasta -input variant_raw_joint.vcf -mode SNP --ts_filter_level 99.5 -recalFile recalibrate_SNP.recal -tranchesFile recalibrate_SNP.tranches -o recalibrated_snps_raw_indels.vcf
### 4. Prepare recalibration parameters for Indels
### 5. Build the Indel recalibration model
gatk -T VariantRecalibrator -R ucsc.hg19.fasta -input recalibrated_snps_raw_indels.vcf -resource:mills,known=false,training=true,truth=true,prior=12.0 Mills_and_1000G_gold_standard.indels.hg19.sites.vcf -resource:dbsnp,known=true,training=false,truth=false,prior=2.0 dbsnp_138.hg19.vcf -an QD -an FS -an SOR -an MQRankSum -an ReadPosRankSum -an InbreedingCoeff -mode INDEL -tranche 100.0 -tranche 99.9 -tranche 99.0 -tranche 90.0 --maxGaussians 4 -recalFile recalibrate_INDEL.recal -tranchesFile recalibrate_INDEL.tranches -rscriptFile recalibrate_INDEL_plots.R
#### 6. Apply the desired level of recalibration to the Indels in the call set
gatk -T ApplyRecalibration -R ucsc.hg19.fasta -input recalibrated_snps_raw_indels.vcf -mode INDEL --ts_filter_level 99.0 -recalFile recalibrate_INDEL.recal -tranchesFile recalibrate_INDEL.tranches -o recalibrated_variants.vcf
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