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Activity Number: 137 - Statistical Methods for Analyzing Genetic Variants and QTLs
Type: Contributed
Date/Time: Monday, July 29, 2019 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #307007
Title: Flexible Approach for Gene-Level Genetic Analysis via Combinations of Summary Statistics
Author(s): Dmitri Zaykin* and Olga Vsevolozhskaya
Companies: National Institute of Environmental Health Sciences and University of Kentucky
Keywords: summary association statistics; reference panel LD structure; genome-wide associations; chi-square type mixture; gene-base analysis; pathway analysis

Difficulties in management and aggregation of individual records or various privacy concerns make methods based on summary statistics (MBSS) particularly appealing. Applications of MBSS in genetic epidemiology include methods for combining signals across SNPs into a gene-, a haplotype block- or a pathway-level association. While combining SNP-level statistics is often as powerful as the analysis of pooled data, one needs to account for linkage disequilibrium (LD) among SNPs and for the correlation between SNPs and covariates. With no access to the original data, methods that incorporate LD information from reference panels to account for the correlation among statistics have to be employed. However, even if the original data and the reference panel stem from the same population, sampling errors introduce differences in estimated LD, leading to bias. Here, we derive a robust approximation to the distribution of sums of test statistics that can be obtained from averages of pairwise LD. This approximation allows one to perform fast and rigorous gene-based computations, resulting in improved power and type I error, without reliance on LD information from a reference population.

Authors who are presenting talks have a * after their name.

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