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A Novel Bayesian Change-point Algoritme for genom-dækkende analyse af Diverse ChIPseq Datatyper
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JoVE Journal Biology
A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

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

DOI:
10.3791/4273-v

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12:39 min

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December 10, 2012

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, , ,
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

Chapters

  • 00:05Title
  • 02:43Preprocessing: Preparing Input Files for Bayesian Change-point (BCP) Analysis & ChIP Read Densities for Detection of Enriched Islands in Diffuse Data
  • 04:48Estimating the Posterior Mean Read Density of Each Block using BCMIX Approximation
  • 06:24Post-processing Posterior Means of Diffuse Read Profiles
  • 07:06Results: Comparison of BCP and SICER in Analysis of Histone Modification Data
  • 11:47Conclusion

Summary

Automatic Translation

Automatic Translation

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.

Tags

Bayesian Change-point AlgorithmGenome-wide AnalysisChIPseq Data TypesProtein-DNA InteractionsRead Density ProfilesPeaksTranscription FactorsHistone ModificationsStatistical ModelsHidden Markov Models (HMMs)Ad Hoc ParametersResolutionUsabilityParameter Estimation ProceduresFinite State Classifications

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