HPeak swMATH ID: 29576 Software Authors: Qin ZS, Yu J, Shen J, et al. Description: HPeak: an HMM-based algorithm for defining read-enriched regions in ChIP-Seq data. Results: Here we introduce HPeak, a H idden Markov model (HMM)-based Peak-finding algorithm for analyzing ChIP-Seq data to identify protein-interacting genomic regions. In contrast to the majority of available ChIP-Seq analysis software packages, HPeak is a model-based approach allowing for rigorous statistical inference. This approach enables HPeak to accurately infer genomic regions enriched with sequence reads by assuming realistic probability distributions, in conjunction with a novel weighting scheme on the sequencing read coverage. Conclusions: Using biologically relevant data collections, we found that HPeak showed a higher prevalence of the expected transcription factor binding motifs in ChIP-enriched sequences relative to the control sequences when compared to other currently available ChIP-Seq analysis approaches. Additionally, in comparison to the ChIP-chip assay, ChIP-Seq provides higher resolution along with improved sensitivity and specificity of binding site detection. Additional file and the HPeak program are freely available at http://www.sph.umich.edu/csg/qin/HPeak. Homepage: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-369 Related Software: BayesPeak; CLIPZ; COUNT; Velvet; ARACHNE; SpliceTrap; DWE; mirTools; miRExpress; TargetSpy; miRNAkey; PatMaN; SeqBuster; ProMiR II; MiRonTop; MiPred; miRanalyzer; DIANA-mirExTra; MiRFinder; FindPeaks Cited in: 4 Publications all top 5 Cited by 15 Authors 1 Alhaji, Baba B. 1 Aransay, Ana M. 1 Dai, Hongsheng 1 Hackenberg, Michael 1 Harrison, Andrew P. 1 Hayashi, Yoshiko 1 Lausen, Berthold 1 Ranciati, Saverio 1 Rodríguez-Ezpeleta, Naiara 1 Vinciotti, Veronica 1 Viroli, Cinzia 1 Wang, Tao 1 Wit, Ernst C. 1 Xiao, Guanghua 1 Yun, Jonghyun Cited in 3 Serials 1 Biometrics 1 Journal of Applied Statistics 1 Statistical Applications in Genetics and Molecular Biology Cited in 3 Fields 3 Statistics (62-XX) 3 Biology and other natural sciences (92-XX) 1 General and overarching topics; collections (00-XX) Citations by Year