A hierarchical Bayesian model for inference of copy number variants and their association to gene expression

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dc.citation.firstpage148en_US
dc.citation.issueNumber1en_US
dc.citation.journalTitleThe Annals of Applied Statisticsen_US
dc.citation.lastpage175en_US
dc.citation.volumeNumber8en_US
dc.contributor.authorCassese, Albertoen_US
dc.contributor.authorGuindani, Micheleen_US
dc.contributor.authorTadesse, Mahlet G.en_US
dc.contributor.authorFalciani, Francescoen_US
dc.contributor.authorVannucci, Marinaen_US
dc.date.accessioned2015-03-16T16:56:10Zen_US
dc.date.available2015-03-16T16:56:10Zen_US
dc.date.issued2014en_US
dc.description.abstractA number of statistical models have been successfully developed for the analysis of high-throughput data from a single source, but few methods are available for integrating data from different sources. Here we focus on integrating gene expression levels with comparative genomic hybridization (CGH) array measurements collected on the same subjects. We specify a measurement error model that relates the gene expression levels to latent copy number states which, in turn, are related to the observed surrogate CGH measurements via a hidden Markov model. We employ selection priors that exploit the dependencies across adjacent copy number states and investigate MCMC stochastic search techniques for posterior inference. Our approach results in a unified modeling framework for simultaneously inferring copy number variants (CNV) and identifying their significant associations with mRNA transcripts abundance. We show performance on simulated data and illustrate an application to data from a genomic study on human cancer cell lines.en_US
dc.identifier.citationCassese, Alberto, Guindani, Michele, Tadesse, Mahlet G., et al.. "A hierarchical Bayesian model for inference of copy number variants and their association to gene expression." <i>The Annals of Applied Statistics,</i> 8, no. 1 (2014) Institute of Mathematical Statistics: 148-175. http://dx.doi.org/10.1214/13-AOAS705.en_US
dc.identifier.doihttp://dx.doi.org/10.1214/13-AOAS705en_US
dc.identifier.urihttps://hdl.handle.net/1911/79352en_US
dc.language.isoengen_US
dc.publisherInstitute of Mathematical Statisticsen_US
dc.rightsThis is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by the Institute of Mathematical Statistics.en_US
dc.subject.keywordBayesian hierarchical modelsen_US
dc.subject.keywordcomparative genomic hybridization arraysen_US
dc.subject.keywordgene expressionen_US
dc.subject.keywordhidden Markov modelsen_US
dc.subject.keywordmeasurement erroren_US
dc.subject.keywordvariable selectionen_US
dc.titleA hierarchical Bayesian model for inference of copy number variants and their association to gene expressionen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpost-printen_US
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