Increased peak detection accuracy in over-dispersed ChIP-seq data with supervised segmentation models.

ABSTRACT:

Background

Histone modification constitutes a basic mechanism for the genetic regulation of gene expression. In early 2000s, a powerful technique has emerged that couples chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq). This technique provides a direct survey of the DNA regions associated to these modifications. In order to realize the full potential of this technique, increasingly sophisticated statistical algorithms have been developed or adapted to analyze the massive amount of data it generates. Many of these algorithms were built around natural assumptions such as the Poisson distribution to model the noise in the count data. In this work we start from these natural assumptions and show that it is possible to improve upon them.

Results

Our compa

SUBMITTER: Liehrmann A 

PROVIDER: S-EPMC8201703 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature