CNV-guided multi-read allocation for ChIP-seq.

ABSTRACT:

Motivation

In chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) and other short-read sequencing experiments, a considerable fraction of the short reads align to multiple locations on the reference genome (multi-reads). Inferring the origin of multi-reads is critical for accurately mapping reads to repetitive regions. Current state-of-the-art multi-read allocation algorithms rely on the read counts in the local neighborhood of the alignment locations and ignore the variation in the copy numbers of these regions. Copy-number variation (CNV) can directly affect the read densities and, therefore, bias allocation of multi-reads.

Results

We propose cnvCSEM (CNV-guided ChIP-Seq by expectation-maximization algorithm), a flexible framework that incorpora

SUBMITTER: Zhang Q 

PROVIDER: S-EPMC4184254 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature