Copy number variation detection using next generation sequencing read counts.

ABSTRACT:

Background

A copy number variation (CNV) is a difference between genotypes in the number of copies of a genomic region. Next generation sequencing (NGS) technologies provide sensitive and accurate tools for detecting genomic variations that include CNVs. However, statistical approaches for CNV identification using NGS are limited. We propose a new methodology for detecting CNVs using NGS data. This method (henceforth denoted by m-HMM) is based on a hidden Markov model with emission probabilities that are governed by mixture distributions. We use the Expectation-Maximization (EM) algorithm to estimate the parameters in the model.

Results

A simulation study demonstrates that our proposed m-HMM approach has greater power for detecting copy number gains and losses relative to ex

SUBMITTER: Wang H 

PROVIDER: S-EPMC4021345 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature