Statistical modeling of coverage in high-throughput data
- PMID: 23872969
- DOI: 10.1007/978-1-62703-514-9_4
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.
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