title: Modeling read counts for CNV detection in exome sequencing data.
abstract: Varying depth of high-throughput sequencing reads along a chromosome makes it possible to observe copy number variants (CNVs) in a sample relative to a reference. In exome and other targeted sequencing projects, technical factors increase variation in read depth while reducing the number of observed locations, adding difficulty to the problem of identifying CNVs. We present a hidden Markov model for detecting CNVs from raw read count data, using background read depth from a control set as well as other positional covariates such as GC-content. The model, exomeCopy, is applied to a large chromosome X exome sequencing project identifying a list of large unique CNVs. CNVs predicted by the model and experimentally validated are then recovered using a cross-platform control set from publicly available exome sequencing data. Simulations show high sensitivity for detecting heterozygous and homozygous CNVs, outperforming normalization and state-of-the-art segmentation methods.
authors.affiliation: Max Planck Institute for Molecular Genetics.
authors.forename: Michael I
authors.initials: MI
authors.lastname: Love
authors.forename: Alena
authors.initials: A
authors.lastname: Myšičková
authors.forename: Ruping
authors.initials: R
authors.lastname: Sun
authors.forename: Vera
authors.initials: V
authors.lastname: Kalscheuer
authors.forename: Martin
authors.initials: M
authors.lastname: Vingron
authors.forename: Stefan A
authors.initials: SA
authors.lastname: Haas
mesh_terms: D000465:Algorithms; D001482:Base Composition; D041321:Chromosomes, Human, X / Q000235:genetics; D003198:Computer Simulation; D056915:DNA Copy Number Variations; D030541:Databases, Genetic; D059472:Exome; D005787:Gene Frequency; D006580:Genetic Carrier Screening; D006720:Homozygote; D006801:Humans; D008390:Markov Chains; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D017422:Sequence Analysis, DNA / Q000379:methods*