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SUMMARY:Detecting Epistatic Selection in the Genome of RILs via a latent G
 aussian Copula Graphical Model - Pariya Behrouzi (University of Groningen)
DTSTART:20160825T094000Z
DTEND:20160825T100000Z
UID:TALK67053@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Recombinant Inbred Lines (RILs) derived from divergent parenta
 l lines can display extensive segregation distortion and long-range linkag
 e disequilibrium (LD) between distant loci on same or different chromosome
 s. These genomic signatures are consistent with epistatic selection having
  acted on entire networks of interacting parental alleles during inbreedin
 g. The reconstruction of these interaction networks from observations of p
 air-wise marker-marker correlations or pair-wise genotype frequency distor
 tions is challenging as multiple testing approaches are under-powered and 
 true long-range LD is difficult to distinguish from drift\, particularly i
 n small RIL panels. Here we develop an efficient method for reconstructing
  an underlying network of genomic signatures of high-dimensional epistatic
  selection from multi-locus genotype data. The network captures the condit
 ionally dependent short- and long-range LD structure of RIL genomes and th
 us reveals "aberrant" marker-marker associations that are due to epistatic
  selection rather than gametic linkage. The network estimation relies on p
 enalized Gaussian copula graphical models\, which accounts for large numbe
 r of markers p and small number of individuals n. A multi-core implementat
 ion of our algorithm makes it feasible to estimate the graph in high-dimen
 sions (max markers ~ 3000). We demonstrate the efficiency of the proposed 
 method on simulated datasets as well as on genotyping data in A.thaliana a
 nd Maize.
LOCATION:Seminar Room 1\, Newton Institute
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