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A signal–noise model for significance analysis of ChIP-seq with negative control

2010; Oxford University Press; Volume: 26; Issue: 9 Linguagem: Inglês

10.1093/bioinformatics/btq128

1367-4811

Xu Han, Lusy Handoko, Xueliang Wei, Chaopeng Ye, Jianpeng Sheng, Chia‐Lin Wei, Feng Lin, Wing‐Kin Sung,

RNA and protein synthesis mechanisms

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.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.http://cmb.gis.a-star.edu.sg/ChIPSeq/tools.htm.