Modeling ChIP sequencing in silico with applications.

PLoS Computational Biology
Zhengdong D ZhangMark Gerstein

Abstract

ChIP sequencing (ChIP-seq) is a new method for genomewide mapping of protein binding sites on DNA. It has generated much excitement in functional genomics. To score data and determine adequate sequencing depth, both the genomic background and the binding sites must be properly modeled. To develop a computational foundation to tackle these issues, we first performed a study to characterize the observed statistical nature of this new type of high-throughput data. By linking sequence tags into clusters, we show that there are two components to the distribution of tag counts observed in a number of recent experiments: an initial power-law distribution and a subsequent long right tail. Then we develop in silico ChIP-seq, a computational method to simulate the experimental outcome by placing tags onto the genome according to particular assumed distributions for the actual binding sites and for the background genomic sequence. In contrast to current assumptions, our results show that both the background and the binding sites need to have a markedly nonuniform distribution in order to correctly model the observed ChIP-seq data, with, for instance, the background tag counts modeled by a gamma distribution. On the basis of these results,...Continue Reading

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Methods Mentioned

BETA
immunoprecipitation
ChIP
ChIP-chip
ChIP-seq
electrophoresis
in

Software Mentioned

JASPAR
TRANSFAC
MEME
R
RepeatMaster
ChIP
Meta
Perl

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