Hi,
After running Mutect2 on tumor/normal paired bam files, I get an output VCF with unusually high depth counts. I understand that the numbers here can differ from the input bam depths due to genotype reassembly within Mutect2. However, these depths are sometimes jumping from around 20 reads to 200 reads, which seems hard to believe. In order to investigate further, I re-ran Mutect2 with the -bamout option, in order to analyze some positions in IGV. The Mutect2 command is posted below. The problem is that when I look at the output bam (bamout) and the output VCF in IGV, the numbers do not match. Note: I ran FilterMutectCalls and selected only PASS calls when deciding which positions to look at. An example position: depth 146 and 192 in tumor and normal, respectively in the VCF, but only 41 reads for the same position in the bamout file.
Questions:
1) What can explain the discrepancy between the bamout depths and the vcf depths?
2) Is there a way to get a bam/bamout that matches the VCF exactly?
Thanks a lot,
Sujay
Mutect2 command:
./gatk-4.0.10.1/gatk --java-options "-Xmx4g" Mutect2 -R /genomes/Hsapiens/hg19/seq/hg19.fa --annotation ClippingRankSumTest --annotation DepthPerSampleHC --annotation MappingQualityRankSumTest --annotation MappingQualityZero --annotation QualByDepth --annotation ReadPosRankSumTest --annotation RMSMappingQuality --annotation FisherStrand --annotation MappingQuality --annotation DepthPerAlleleBySample --annotation Coverage --read-validation-stringency LENIENT -I tumorX.markduplicates.grouped.bam -tumor tumorX -I normalX.markduplicates.grouped.bam -normalX normal -L ./baits.bed --interval-set-rule INTERSECTION --disable-read-filter NotDuplicateReadFilter -ploidy 2 -bamout tumorX.bamout.bam -O tumorX.vcf