Please use this identifier to cite or link to this item: https://doi.org/10.1093/bioinformatics/btq128
Title: A signal-noise model for significance analysis of ChIP-seq with negative control
Authors: Xu, H.
Handoko, L.
Wei, X.
Ye, C.
Sheng, J.
Wei, C.-L.
Lin, F.
Sung, W.-K. 
Issue Date: 2010
Source: Xu, H., Handoko, L., Wei, X., Ye, C., Sheng, J., Wei, C.-L., Lin, F., Sung, W.-K. (2010). A signal-noise model for significance analysis of ChIP-seq with negative control. Bioinformatics 26 (9) : 1199-1204. ScholarBank@NUS Repository. https://doi.org/10.1093/bioinformatics/btq128
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. Contact: sungk@gis.a-star.edu.sg; asflin@ntu.edu.sg. Supplementary Information:Supplementary data are available at Bioinformatics online. © The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org.
Source Title: Bioinformatics
URI: http://scholarbank.nus.edu.sg/handle/10635/39478
ISSN: 13674803
DOI: 10.1093/bioinformatics/btq128
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