The Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding

BMC Bioinformatics

Methodology Article

Morten Beck Rye¹  Tony Håndstad¹  Finn Drabløs¹  Karl Kornacker² 

[1] Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), P.O. Box 8905, NO-7491, Trondheim, Norway;Division of Sensory Biophysics, Ohio State University, Columbus, OH, USA;

关键词: ChIP-Seq;    Peak finding;    Benchmark;    Repeats;   

DOI  :  10.1186/1471-2105-13-176

 received in 2012-01-03, accepted in 2012-06-21,  发布年份 2012

来源: Springer

【 摘 要 】

BackgroundChromatin immunoprecipitation combined with high-throughput sequencing (ChIP-Seq) is the most frequently used method to identify the binding sites of transcription factors. Active binding sites can be seen as peaks in enrichment profiles when the sequencing reads are mapped to a reference genome. However, the profiles are normally noisy, making it challenging to identify all significantly enriched regions in a reliable way and with an acceptable false discovery rate.ResultsWe present the Triform algorithm, an improved approach to automatic peak finding in ChIP-Seq enrichment profiles for transcription factors. The method uses model-free statistics to identify peak-like distributions of sequencing reads, taking advantage of improved peak definition in combination with known characteristics of ChIP-Seq data.ConclusionsTriform outperforms several existing methods in the identification of representative peak profiles in curated benchmark data sets. We also show that Triform in many cases is able to identify peaks that are more consistent with biological function, compared with other methods. Finally, we show that Triform can be used to generate novel information on transcription factor binding in repeat regions, which represents a particular challenge in many ChIP-Seq experiments. The Triform algorithm has been implemented in R, and is available via http://tare.medisin.ntnu.no/triform.

【 授权许可】

Unknown   
© Kornacker et al.; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.