[bioinfo] FW: [Statnote] Dept of Statistics Seminar: May 1, 2009

[Sinha, Saurabh]

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>   Statistical seminar: ``A Bayesian Partition Model for Detecting eQTL
> Modules" by Jun S. Liu, Harvard University
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>       Speaker        Jun S. Liu, Harvard University
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>       Date       Friday, May 1, 2009
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>       Time       3:00 pm  
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>       Location       HAB 156 (special location)
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>       Sponsor       Department of Statistics (special time and special
> location)   
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>       Event type       Seminar
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>       Original Calendar       Department of Statistics
> <http://illinois.edu/calendar/Calendar?calId=1439>
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>   Studies of the relationship between genomic DNA variation and gene
> expression variation, often referred to as expression quantitative trait loci
> (eQTL) mapping, has been conducted in many species and resulted in many
> significant findings. Because of the large number of genes and genetic markers
> in such analyses, it is extremely challenging to discover how a small number
> of eQTLs interact with each other to affect mRNA expression levels for a set
> of (most likely co-regulated) genes. We present a Bayesian method to
> facilitate the task, in which co-expressed genes mapped to a common set of
> markers are treated as a module characterized by latent indicator variables. A
> Markov chain Monte Carlo algorithm is designed to search simultaneously for
> the module genes and their linked markers. We show by simulations that this
> method is much more powerful for detecting true eQTLs and their target genes
> than traditional QTL mapping methods. We applied the procedure to a data set
> consisting of gene expression and genotypes for 112 segregants of S.
> cerevisiae and identified modules containing genes mapped to previously
> reported eQTL hot spots, dissected these large eQTL hot spots into refined
> modules with biological implications, and discovered a few epistasis modules.
> If time permits, I will also discuss a few ideas regarding Bayesian modeling
> and discovery of interactions among a large number of variables in a
> classification or regression framework.
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> 
> 
> -- 
> Ping Ma
> Assistant Professor, Department of Statistics
> Beckman Fellow, Center for Advanced Study
> Faculty Member, Institute for Genomic Biology  
> University of Illinois at Urbana-Champaign

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