title: The allele distribution in next-generation sequencing data sets is accurately described as the result of a stochastic branching process.
abstract: With the availability of next-generation sequencing (NGS) technology, it is expected that sequence variants may be called on a genomic scale. Here, we demonstrate that a deeper understanding of the distribution of the variant call frequencies at heterozygous loci in NGS data sets is a prerequisite for sensitive variant detection. We model the crucial steps in an NGS protocol as a stochastic branching process and derive a mathematical framework for the expected distribution of alleles at heterozygous loci before measurement that is sequencing. We confirm our theoretical results by analyzing technical replicates of human exome data and demonstrate that the variance of allele frequencies at heterozygous loci is higher than expected by a simple binomial distribution. Due to this high variance, mutation callers relying on binomial distributed priors are less sensitive for heterozygous variants that deviate strongly from the expected mean frequency. Our results also indicate that error rates can be reduced to a greater degree by technical replicates than by increasing sequencing depth.
authors: Institute for Medical and Human Genetics, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
authors: Verena
authors: V
authors: Heinrich
authors: Jens
authors: J
authors: Stange
authors: Thorsten
authors: T
authors: Dickhaus
authors: Peter
authors: P
authors: Imkeller
authors: Ulrike
authors: U
authors: Krüger
authors: Sebastian
authors: S
authors: Bauer
authors: Stefan
authors: S
authors: Mundlos
authors: Peter N
authors: PN
authors: Robinson
authors: Jochen
authors: J
authors: Hecht
authors: Peter M
authors: PM
authors: Krawitz
mesh_terms: D000483:Alleles; D059472:Exome; D005787:Gene Frequency; D006579:Heterozygote; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D017422:Sequence Analysis, DNA; D013269:Stochastic Processes