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Bioinformatics. 2010 May 1;26(9):1199-204. doi: 10.1093/bioinformatics/btq128. Epub 2010 Apr 5.

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

Author information

  • 1Genome Institute of Singapore, Singapore.

Abstract

MOTIVATION:

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.

AVAILABILITY:

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

PMID:
20371496
[PubMed - indexed for MEDLINE]
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