Problem with annovar in GATK4 output

Question

[ahmad mousavi]

Hello

Based on GATK4 best practices pipline I have made a VCF file composed 4 person WES data. When I want to annotate it with annovar , but annovar could not annotate all variations and near 70% of variations discard and gone to Invalid_input.

I though it might happen due to VCF version (4.2), but it doesn't work with annovar default input format (avinput).

What is your suggestion for annotating GATK4 output VCFs?

[Kevin Blighe]

Please paste some of the variants that are stored in invalid_input

A better approach may be to first split your variants into 4 different avinput files, and then annotate these:

perl annovar/convert2annovar.pl -format vcf4 -withzyg --allsample -outfile WES.ann WES.vcf ;

[ahmad mousavi]

thanks for reply. The problems still exist. I have 5 sample ( output from Haplotypecaller which merged by Bcftools), but after running you command each file is separated and it is hard to track a SNP in all 5 samples.

Can I annotate all 5 samples individually and then merge annotated result into one file?

   perl convert2annovar.pl in.vcf -format vcf4 > output

It gives following information, I lost almost 50,000 SNPs and indels

NOTICE: Finished reading 159791 lines from VCF file NOTICE: A total of 156393 locus in VCF file passed QC threshold, representing 141154 SNPs (99256 transitions and 41898 transversions) and 17068 indels/substitutions NOTICE: Finished writing 93786 SNP genotypes (66143 transitions and 27643 transversions) and 10272 indels/substitutions for 1 sample (but input contains 5 samples)

[Kevin Blighe]

Without seeing your VCF, I cannot understand entirely what is going on. The only filter that could result in substantial loss of variants is the --snpqual <float> filter passed to convert2annovar.pl, with an initial value set to 20.

Other possibilities to consider:

• you have many variants called on contigs outside the main autosomes and sex chromosomes
• you have many entries in your VCF that are 0/0 (i.e., ref calls) but that are still recorded You have a very high proportion of multi-allelic sites

You could indeed process each sample independently with the --allsample flag, and then merge it all back together. You should keep rack of wich variants were called in which individual, though. When sample number is low, I believe that doing it this way is fine.