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A Novel Bayesian Change-point Algoritme for genom-dækkende analyse af Diverse ChIPseq Datatyper
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A Novel Bayesian Change-point Algoritme for genom-dækkende analyse af Diverse ChIPseq Datatyper

Article DOI: 10.3791/4273-v • 12:39 min • December 10th, 2012
December 10th, 2012 •
1, 1,2, 1,2, 2,3
1Department of Applied Mathematics & Statistics, Stony Brook University, 2Computational Biology and Bioinformatics, Cold Spring Harbor Laboratory, 3Department of Molecular and Cell Biology, University of Texas at Dallas

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Vores Bayesian Change Point (BCP) algoritme bygger på state-of-the-art fremskridt i modellering skift-point via Hidden Markov Models og anvender dem til chromatin immunoprecipitation sekventering (ChIPseq) dataanalyse. BCP klarer sig godt i både brede og punktformig datatyper, men excellerer i præcist at identificere robuste, reproducerbare øer af diffus histon berigelse.

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Genetik Bioinformatik Genomics Molekylærbiologi Cellular Biology Immunology Kromatin immunopræcipitation chip-Seq histon ændringer segmentering Bayesian skjulte Markov modeller epigenetik
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