Estimate read depth to further filter the somatic calls #156
Description
Feature request
Context
From one xavier user:
Hello, we previously evaluated somatic mutations in gallbladder cancer samples with paired germline samples using whole exome sequencing (Please see attached). This was previously aligned to hg19. We are about to receive new liquid biopsy data for these samples, thus I want to update the prior analyses. I took the WES data and ran them through XAVIER and aligned to hg38. I then took the combined mutation MAF file, loaded it into R using maftools, and applied the following filters and only selected calls from 2 or more callers: filtered_maf <- subsetMaf( maf = maf_data, query = "FILTER == 'PASS' & t_depth >= 8 & t_alt_count >= 3 & n_depth >= 6 & (t_alt_count / t_depth) >= 0.05 & # Tumor VAF ≥ 5% (n_alt_count / n_depth) <= 0.02 & # Normal VAF ≤ 2% (is.na(gnomAD_AF) | gnomAD_AF < 0.01) & BIOTYPE == 'protein_coding'") When I did this, some of the usual genes showed up as top hits, but the tumor mutational burden is way too high. From the XAVIER output, I was wondering if you had any additional guidance on how to further filter the calls?
Proposed solution
Calculate the read depth of reference and alternate alleles around somatic mutations to see if there's enough read depth supporting a given mutation