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Public Lecture

Mathematical and Computational Approaches in High-Throughput Genomics

Workshop IV: Coancestry, Association, and Population Genomics

November 29 - December 2, 2011


Organizing Committee | Scientific Overview | Speaker List

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Organizing Committee

Carlos Bustamante (Stanford University)
Eleazar Eskin (University of California, Los Angeles (UCLA), Computer Science)
Steve Evans (University of California, Berkeley (UC Berkeley), Statistics)
Phil Green (University of Washington)
Elizabeth Thompson (University of Washington)

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Scientific Overview

Statistical and population genetics have always been rich in mathematical challenges. The recent availability of sequence from 1000s of human genomes, only increases these challenges. These data will provide unprecedented opportunity to analyze the structure of the human population and understand how genetic variation affects traits. Increasingly, recent studies show that the genomes of modern individuals are shaped by many forces including complex patterns of ancestry from multiple ancestral populations, ancient migration patterns and spatial structure of human population. This sequence data provides opportunities to study, model, and analyze the complex genetic structure of the human population and the processes of mutation and selection that have established and maintain human variation. Increasingly, inherited variants of interest are not simply DNA base changes, but include copy-number variants (small duplications or deletions), inversions, and the products of gene conversion.

Over the last few years, Genome Wide Association Studies (GWAS) have been a central tool for elucidating the connections between genetic variation and traits. While in the past the genetic variation has consisted of Single Nucleotide Polymorphism arrays (which collect only the common variants), in the coming years this will likely switch to whole genome sequencing which will provide the opportunity to understand how rare variation affects traits.

This workshop focuses on mathematical challenges in analyzing human variation data and its affect on traits both from sequences and SNP arrays. Topics include mathematical, statistical and computational challenges in modeling human populations and admixture, spatial population structure, as well as development of techniques for analysis of genome-wide association studies, gene-gene interactions, gene-environment interactions, and rare variation effects on traits.

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Confirmed Speakers

Carlos Bustamante (Stanford University)
Nilanjan Chatterjee (National Cancer Institute)
Andrew Clark (Cornell University)
Richard Durbin (Sanger Institute)
Daniel Geschwind (University of California, Los Angeles (UCLA))
Eran Halperin (Tel Aviv University)
Iuliana Ionita (Columbia University)
Suzanne Leal (Baylor College of Medicine)
Hongzhe Li (University of Pennsylvania)
Rasmus Nielsen (University of California, Berkeley (UC Berkeley))
John Novembre (University of California, Los Angeles (UCLA))
Nick Patterson (Massachusetts Institute of Technology)
Itsik Pe'er (Columbia University)
Kathryn Roeder (Carnegie-Mellon University)
Noah Rosenberg (Stanford University)
Chiara Sabatti (Stanford University)
Montgomery Slatkin (University of California, Berkeley (UC Berkeley))
Yun Song (University of California, Berkeley (UC Berkeley))
Matthew Stephens (University of Chicago)

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Contact Us:

Institute for Pure and Applied Mathematics (IPAM)
Attn: GENWS4
460 Portola Plaza
Los Angeles CA 90095-7121
Phone: 310 825-4755
Fax: 310 825-4756
Email: ipam@ucla.edu
Website: http://www.ipam.ucla.edu/programs/genws4/

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