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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
Nuestro punto de cambio bayesiano (BCP) algoritmo se basa en los avances del estado de la técnica de modelado en los puntos de cambio a través de modelos ocultos de Markov y los aplica a la cromatina immunoprecipitation secuenciación (ChIPseq) el análisis de datos. BCP funciona bien en ambos tipos de datos amplios y punteada, pero sobresale en la identificación precisa de las islas robustas, reproducibles de enriquecimiento histona difusa.
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
