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Old 11-19-2014, 02:41 AM   #5
vd4mindia
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Location: Milan

Join Date: May 2013
Posts: 40
Default Filtering varscan variants

I would like to ask removing the snps closer to indels at 1bp thus removes a lot of snps for me. But it is not a test for false positive right? I believe if am using the local realignment around indel step with with GATK so the mis matches due to indel should not be a reason to work if you used GATK processed bam files for varscan and other standard variant calling tools. I am having typical normal/tumor sequenced at 70X for which I am calling variants with the varscan and if I do the somaticfilter with the sample.snp and sample.indel I lose a lot of SNPs. I get around 200 variants for my sample which I was thinking to be good numbers but then on annotating I miss out most on the exons. Also when I compare this results with mutect I do not get most of the mutations I receive with Mutect. So I ran again the VarScan with below command

Code:
samtools mpileup -f /scratch/GT/vdas/test_exome/exome/hg19.fa -q 1 -B /scratch/GT/vdas/pietro/exome_seq/results/N_S8980/N_S8980.realigned.recal.bam /scratch/GT/vdas/pietro/exome_seq/results/T_S7998/T_S7998.realigned.recal.bam | java -Xmx14G -jar /scratch/GT/softwares/VarScan.v2.3.6.jar somatic - /scratch/GT/vdas/pietro/exome_seq/results/varscan_out_17112014/S_313_T_soma_vcf.output --output-vcf 1 --mpileup 1 --min-var-freq 0.05 --min-coverage-normal 10 --min-coverage-tumor 8 --p-value 0.05
Now am getting the sample.snps.vcf with over 11k variants. I am thinking of not using somaticfilter, rather use process somatic to have the high confidence snps and then use filtervariant.py script to extract most confident ones. How does this sound?
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