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.
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.
Authors: Ildiko Györy; Sören Boller; Robert Nechanitzky; Elizabeth Mandel; Sebastian Pott; Edison Liu; Rudolf Grosschedl Journal: Genes Dev Date: 2012-03-19 Impact factor: 11.361
Authors: Sebastian Schröder; Eva Herker; Friederike Itzen; Daniel He; Sean Thomas; Daniel A Gilchrist; Katrin Kaehlcke; Sungyoo Cho; Katherine S Pollard; John A Capra; Martina Schnölzer; Philip A Cole; Matthias Geyer; Benoit G Bruneau; Karen Adelman; Melanie Ott Journal: Mol Cell Date: 2013-11-07 Impact factor: 17.970
Authors: Tamás Schauer; Petra C Schwalie; Ava Handley; Carla E Margulies; Paul Flicek; Andreas G Ladurner Journal: Cell Rep Date: 2013-10-03 Impact factor: 9.423
Authors: Andrew C Nelson; Nischalan Pillay; Stephen Henderson; Nadège Presneau; Roberto Tirabosco; Dina Halai; Fitim Berisha; Paul Flicek; Derek L Stemple; Claudio D Stern; Fiona C Wardle; Adrienne M Flanagan Journal: J Pathol Date: 2012-09-26 Impact factor: 7.996