title: Statistical modeling of coverage in high-throughput data.
abstract: In high-throughput sequencing experiments, the number of reads mapping to a genomic region, also known as the "coverage" or "coverage depth," is often used as a proxy for the abundance of the underlying genomic region in the sample. The abundance, in turn, can be used for many purposes including calling SNPs, estimating the allele frequency in a pool of individuals, identifying copy number variations, and identifying differentially expressed shRNAs in shRNA-seq experiments.In this chapter we describe the fundamentals of statistical modeling of coverage depth and discuss the problems of estimation and inference in the relevant experimental scenarios.
authors.affiliation: School of Mathematical Sciences, Tel Aviv University, Tel Aviv, Israel.
authors.forename: David
authors.initials: D
authors.lastname: Golan
authors.forename: Saharon
authors.initials: S
authors.lastname: Rosset
mesh_terms: D000818:Animals; D056915:DNA Copy Number Variations; D005787:Gene Frequency; D016678:Genome; D023281:Genomics / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D020641:Polymorphism, Single Nucleotide