The allele distribution in next-generation sequencing data sets is accurately described as the result of a stochastic branching process
作者： Verena Heinrich , Jens Stange , Thorsten Dickhaus , Peter Imkeller , Ulrike Krüger
DOI: 10.1093/NAR/GKR1073
关键词:
摘要: 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 deeper understanding distribution variant call frequencies at heterozygous loci in NGS data sets prerequisite for sensitive detection. We model crucial steps an protocol as stochastic branching process and derive mathematical framework alleles before measurement sequencing. confirm our theoretical results by analyzing technical replicates human exome variance allele higher than simple binomial distribution. Due to this high variance, mutation callers relying distributed priors are less deviate strongly from mean frequency. Our also indicate error rates can reduced greater degree increasing depth.
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