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제목 [학술세미나] [학과세미나] 11월 6일(금) 학과세미나 안내
작성일 2020-11-02 08:10:21
내용 [학과세미나] 11월 6일(금) 학과세미나 안내

▪제목 : Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies
▪연사 : 송민선 (숙명여대 통계학과)
▪일시 : 2020년 11월 6일(금) AM 11:00 – 12:00
▪진행 : ZOOM 활용 비대면 세미나
(접속 링크 : https://snu-ac-kr.zoom.us/j/83667177969)
 
초 록
Genome-wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene-environment interactions. We focus on case-control association studies where inference for an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene-environment independence in the underlying population. As increasingly large-scale GWAS are being performed through consortia effort where it is preferable to share only summary-level information across studies, we also describe simple mechanisms for implementing score tests based on standard meta-analysis of "one-step" maximum-likelihood estimates across studies. Applications of the methods in simulation studies and a dataset from GWAS of lung cancer illustrate ability of the proposed methods to maintain type-I error rates for the underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, the retrospective methods can lead to considerable efficiency gain for modeling of gene-environment interactions under the assumption of gene-environment independence. Methods are made available for public use through CGEN R software package.
 
파일 세미나 안내_201106_송민선.hwp [15KB]