|
Activity Number:
|
486
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Thursday, August 7, 2008 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Biometrics Section
|
| Abstract - #301089 |
|
Title:
|
Rapid Genotype Imputation and Analysis of Resequencing Data Using Markov Models
|
|
Author(s):
|
Yun Li*+ and Cristen Willer and Jun Ding and Paul Scheet and Goncalo Abecasis
|
|
Companies:
|
The University of Michigan and The University of Michigan and The University of Michigan and The University of Michigan and The University of Michigan
|
|
Address:
|
1071 Barton Dr Apt205, Ann Arbor, MI, 48105,
|
|
Keywords:
|
genotype imputation ; GWAS ; Markov model ; meta-analysis ; resequencing ; gene mapping
|
|
Abstract:
|
I propose and implement efficient Markov models for genome wide association studies (GWAS), a more powerful tool to detect genetic variants with small individual contributions to complex traits. Specifically, I consider how to impute several million common SNPs not typed in a GWAS. Imputation-enabled meta-analyses identified multiple novel loci influencing risk of diabetes, coronary artery disease, height, or lipid levels. I also consider how to obtain accurate estimates of individual sequences from shotgun resequencing data. My method allows the more cost-effective more-individual-lower-coverage design both for generating a public resequencing database and for capturing variants in individual resequencing based GWAS. My approach should stimulate the advent of large-scale resequencing based GWAS and foster the detection of rare variants not adequately assessed with current approaches.
|
