The Division of Biostatistics at the Department of Preventive Medicine invites you to attend the following seminar.
Time: Monday, September 18, 2:00 PM-3:00 PM CDT
ZOOM Virtual Room Connection: Register in advance for this meeting
Seminar Website: https://www.eventcreate.com/e/biostatisticsseminar
Speaker Bio: https://learningmalanya.github.io/
Real-time Linear Mixed Model Implementation for Association Mapping on Large Numbers of Quantitative Traits
Zifan (Fred) Yu, M.S.
Bredesen Center, University of Tennessee Knoxville
Linear mixed models (LMMs) are used widely in genome-wide association studies (GWAS) to account for population structure and genetic relatedness among the study individuals. The advancements of high-throughput genotyping technologies have enabled GWAS to be conducted on large number of traits and created a demand for more efficient and scalable implementations of LMMs. We developed a new software package for fast LMM association scans, BulkLMM, that is designed for GWAS of large numbers of quantitative traits with modest sample sizes which are common for analyzing animal model data. We applied BulkLMM on BXD Individual Liver Proteome data, wherefor genome scans of the scale of over 35k traits and 7k markers and obtained real-time (in a few seconds) performance on high-end desktop hardware. BulkLMM provides additional features valuable for performing GWAS, such as permutation testing and the ability to incorporate prior knowledge on the residual variance. Our open-source implementation in the Julia programming language has the combined benefits of high-efficiency and easy prototyping which enable seamless downstream analysis and manipulation.