서울대학교 생물정보학 협동과정 주최로 세미나를 아래와 같이 열고자 하오니 많은 참여 바랍니다.

세미나는 대면 강의로 예정되어 있으며 강의에 참여하고자 하시는 분께서는 아래 일시와 장소를 참고하여 주시길 바랍니다.

일시: 2023년 10월 31일 화요일 오전 11시

연사: 박경택 교수님 (서울대학교 보건환경연구소)

장소: 500동 L304호

(500동건물에서 503동 건물 방향 엘리베이터 이용)

Title: Mixed models for analyzing OMICs data

Abstract

A mixed model, which combines fixed and random effects, is widely employed in OMICs data analysis, primarily for adjusting sample relatedness. SAIGE, a prevalent tool in genome-wide association study (GWAS), utilizes a logistic mixed model with a genomic relationship matrix (GRM) as a random effect. In the first part of this seminar, I will introduce GWAS to identify genetic loci susceptible to nontuberculous mycobacterial pulmonary disease (NTM-PD) in the Korean population. This study uncovered three novel causal loci, with one exclusively detected by SAIGE, potentially playing a crucial role in NTM-PD development. In the subsequent section, I will present algorithm employing a linear mixed model for bulk RNA sequencing (RNA-seq) data analysis, comparing it to existing methods. A new relationship matrix for RNA-seq data was developed to address relatedness among samples, and its application will be demonstrated in both bulk and single cell RNA-seq data analysis.