title: A signal-noise model for significance analysis of ChIP-seq with negative control.
abstract: 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.
authors.affiliation: Genome Institute of Singapore, Singapore.
authors.forename: Han
authors.initials: H
authors.lastname: Xu
authors.forename: Lusy
authors.initials: L
authors.lastname: Handoko
authors.forename: Xueliang
authors.initials: X
authors.lastname: Wei
authors.forename: Chaopeng
authors.initials: C
authors.lastname: Ye
authors.forename: Jianpeng
authors.initials: J
authors.lastname: Sheng
authors.forename: Chia-Lin
authors.initials: CL
authors.lastname: Wei
authors.forename: Feng
authors.initials: F
authors.lastname: Lin
authors.forename: Wing-Kin
authors.initials: WK
authors.lastname: Sung
mesh_terms: 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
chemical_list: D006657:Histones