The impact of collisions on the ability to detect rare mutant alleles using Barcode-Type Next-Generation Sequencing Techniques

Abstract

Barcoding techniques are used to reduce error from next-generation sequencing, with applications ranging from understanding tumor subclone populations to detecting circulating tumor DNA. Collisions occur when more than one sample molecule is tagged by the same unique identifier (UID) and can result in failure to detect very-low-frequency mutations and error in estimating mutation frequency. Here, we created computer models of barcoding technique, with and without amplification bias introduced by the UID, and analyzed the effect of collisions for a range of mutant allele frequencies (1e−6 to 0.2), number of sample molecules (10 000 to 1e7), and number of UIDs (410- 414). Inability to detect rare mutant alleles occurred in 0% to 100% of simulations, depending on collisions and number of mutant molecules. Collisions also introduced error in estimating mutant allele frequency resulting in underestimation of minor allele frequency. Incorporating an understanding of the effect of collisions into experimental design can allow for optimization of the number of sample molecules and number of UIDs to minimize the negative impact on rare mutant detection and mutant frequency estimation.