Statistical modeling of coverage in high-throughput data

David Golan, Saharon Rosset

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


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.

Original languageEnglish
Title of host publicationDeep Sequencing Data Analysis
Number of pages19
StatePublished - 2013

Publication series

NameMethods in Molecular Biology


  • CNV calling
  • Coverage
  • Differential expression
  • High-throughput sequencing
  • Modeling
  • Next-generation sequencing
  • SNP calling
  • Statistical modeling of coverage

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Genetics


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