Title
BayesPeak: Bayesian analysis of ChIP-seq data.
Abstract
High-throughput sequencing technology has become popular and widely used to study protein and DNA interactions. Chromatin immunoprecipitation, followed by sequencing of the resulting samples, produces large amounts of data that can be used to map genomic features such as transcription factor binding sites and histone modifications.Our proposed statistical algorithm, BayesPeak, uses a fully Bayesian hidden Markov model to detect enriched locations in the genome. The structure accommodates the natural features of the Solexa/Illumina sequencing data and allows for overdispersion in the abundance of reads in different regions. Moreover, a control sample can be incorporated in the analysis to account for experimental and sequence biases. Markov chain Monte Carlo algorithms are applied to estimate the posterior distributions of the model parameters, and posterior probabilities are used to detect the sites of interest.We have presented a flexible approach for identifying peaks from ChIP-seq reads, suitable for use on both transcription factor binding and histone modification data. Our method estimates probabilities of enrichment that can be used in downstream analysis. The method is assessed using experimentally verified data and is shown to provide high-confidence calls with low false positive rates.
Year
DOI
Venue
2009
10.1186/1471-2105-10-299
BMC Bioinformatics
Keywords
Field
DocType
bioinformatics,hidden markov model,algorithms,microarrays,chip,markov chain monte carlo,chromatin immunoprecipitation,false positive rate,binding sites,posterior probability,computational biology,dna,transcription factor binding site,proteins,bayes theorem,high throughput,histone modification,posterior distribution,bayesian analysis
Peak calling,Binding site,Biology,Histone,DNA binding site,DNA,Bioinformatics,Chromatin immunoprecipitation,Genetics,DNA microarray,Bayes' theorem
Journal
Volume
Issue
ISSN
10
1
1471-2105
Citations 
PageRank 
References 
40
2.29
11
Authors
4
Name
Order
Citations
PageRank
Christiana Spyrou1452.98
Rory Stark2644.40
Andy G. Lynch31176.06
simon tavare422924.40