Colloquia, Seminars and Conference News
Title : Whole Population, Genomewide Mapping of Hidden Relatedness
Date : September 26, 2008. (11:00 am) Tea starts half an hour before each seminar
Location: ITEB 336
Speaker : Itsik Pe'er
Abstract:
The ability to identify and quantify genealogical relationships between
individuals in a complex population is an important step in accurately
using such data for disease analysis and improving our understanding of
demography. However, exhaustive pair-wise analysis which has been
successful in small cohorts cannot keep up with the current torrent of
genotype data. We present GERMLINE, a robust algorithm for identifying
pairwise segmental sharing which scales linearly with the number of
input individuals. Our approach is based on a dictionary of haplotypes
to efficiently discover short exact matches between individuals and then
expands these matches to identify long nearly-identical segmental
sharing that is indicative of relatedness. We comprehensively survey
hidden relatedness both in the HapMap as well as in a densely typed
island population of 3,000 individuals. We show GERMLINE agrees with
other methods when they can process the data, and facilitates analysis
of larger scale studies. We demonstrate the novel application of precise
analysis of hidden relatedness. We show shared segment discovery can
identify haplotype phasing errors and potentially resolve them. Finally,
we use detected identity of genomic segments for exposing polymorphic
deletions that are otherwise challenging to detect, with 8/14 deletions
in the HapMap samples and 149/200 deletions in the island data having
independent experimental validation.
Bio:Itsik Pe'er received his BSc degree in Math and Computer Science, and MSc and PhD degree in Computer Science from Tel Aviv University. His dissertation on
reconstruction of biological sequences won the Celera award for
PhD in genomics.
He was a postdoctoral researcher at Weizmann Institute of and then at the Broad Institute of Harvard and MIT, working on the Human Haplotype Map project. He is currently at Columbia University, with the Department of Computer Science and Center for Computational Biology and Bioinformatics,
studying computational issues in high throughput genetics.
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