TY - CHAP
T1 - Statistical modeling of coverage in high-throughput data
AU - Golan, David
AU - Rosset, Saharon
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - CNV calling
KW - Coverage
KW - Differential expression
KW - High-throughput sequencing
KW - Modeling
KW - Next-generation sequencing
KW - SNP calling
KW - Statistical modeling of coverage
UR - http://www.scopus.com/inward/record.url?scp=84881105887&partnerID=8YFLogxK
U2 - 10.1007/978-1-62703-514-9_4
DO - 10.1007/978-1-62703-514-9_4
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C2 - 23872969
AN - SCOPUS:84881105887
SN - 9781627035132
T3 - Methods in Molecular Biology
SP - 61
EP - 79
BT - Deep Sequencing Data Analysis
PB - Humana Press Inc.
ER -