A Bayesian Partition Method for Detecting Pleiotropic and Epistatic eQTL Modules

Open Access

Peer-reviewed

Research Article

Wei Zhang,

Affiliation UBS Equities, Stamford, Connecticut, United States of America
⨯
Jun Zhu,

Affiliations Rosetta Inpharmatics, LLC, Merck & Co., Inc., Seattle, Washington, United States of America, Sage Bionetworks, Seattle, Washington, United States of America
⨯
Eric E. Schadt,

Affiliations Sage Bionetworks, Seattle, Washington, United States of America, Pacific Biosciences, Menlo Park, California, United States of America
⨯
Jun S. Liu

* E-mail: jliu@stat.harvard.edu

Affiliation Department of Statistics, Harvard University, Cambridge, Massachusetts, United States of America
⨯

Reader Comments

We seek module partitions in which expression patterns are similar for all genes, and gene expression variations across different individuals can be explained by the individual types.
http://ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000642#article1.body1.sec4.sec1.p2

剖分模型的目的是寻找合适的模型

No competing interests declared.

Gene expression
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Genetic loci
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Epistasis
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Gene mapping
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Markov models
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Yeast
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Gene regulation
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Saccharomyces cerevisiae
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