A signal-noise model for significance analysis of ChIP-seq with negative control.
BACKGROUND
ChIP-seq is becoming the main approach to the genome-wide study of protein-DNA interactions and histone modifications. Existing informatics tools perform well to extract strong ChIP-enriched sites. However, two questions remain to be answered: (i) to which extent is a ChIP-seq experiment able to reveal the weak ChIP-enriched sites? (ii) are the weak sites biologically meaningful? To answer these questions, it is necessary to identify the weak ChIP signals from background noise.


RESULTS
We propose a linear signal-noise model, in which a noise rate was introduced to represent the fraction of noise in a ChIP library. We developed an iterative algorithm to estimate the noise rate using a control library, and derived a library-swapping strategy for the false discovery rate estimation. These approaches were integrated in a general-purpose framework, named CCAT (Control-based ChIP-seq Analysis Tool), for the significance analysis of ChIP-seq. Applications to H3K4me3 and H3K36me3 datasets showed that CCAT predicted significantly more ChIP-enriched sites that the previous methods did. With the high sensitivity of CCAT prediction, we revealed distinct chromatin features associated to the strong and weak H3K4me3 sites.


BACKGROUND
http://cmb.gis.a-star.edu.sg/ChIPSeq/tools.htm.
Xu
Han
H
Genome Institute of Singapore, Singapore.
Handoko
Lusy
L
Wei
Xueliang
X
Ye
Chaopeng
C
Sheng
Jianpeng
J
Wei
Chia-Lin
CL
Lin
Feng
F
Sung
Wing-Kin
WK
D000465:Algorithms; D001665:Binding Sites; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D005786:Gene Expression Regulation; D016678:Genome; D006657:Histones / Q000737:chemistry; D015233:Models, Statistical; D016012:Poisson Distribution; D015203:Reproducibility of Results; D012984:Software
D006657:Histones