Consensus rules in variant detection from next-generation sequencing data

Abstract

A critical step in detecting variants from next-generation sequencing data is post hoc filtering of putative variants called or predicted by computational tools. Here, we highlight four critical parameters that could enhance the accuracy of called single nucleotide variants and insertions/deletions: quality and deepness, refinement and improvement of initial mapping, allele/strand balance, and examination of spurious genes. Use of these sequence features appropriately in variant filtering could greatly improve validation rates, thereby saving time and costs in next-generation sequencing projects. © 2012 Jia et al.