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Incorporating Sex Chromosomes In Transcriptome Prediction Models And Improving Cross-Population Prediction Performance, Daniel S. Araujo
Incorporating Sex Chromosomes In Transcriptome Prediction Models And Improving Cross-Population Prediction Performance, Daniel S. Araujo
Master's Theses
Transcriptome prediction models built with data from European-descent individuals are less accurate when applied to different populations because of differences in linkage disequilibrium patterns and allele frequencies. We hypothesized multivariate adaptive shrinkage may improve cross-population transcriptome prediction, as it leverages effect size estimates across different conditions - in this case, different populations. To test this hypothesis, we made transcriptome prediction models for use in transcriptome-wide association studies (TWAS) using different methods (Elastic Net, Matrix eQTL and Multivariate Adaptive Shrinkage in R (MASHR)) and tested their out-of-sample transcriptome prediction accuracy in population-matched and cross-population scenarios. Additionally, to evaluate model applicability in …
Population-Matched Transcriptome Prediction Increases Discovery And Replication Rate In Twas, Elyse Geoffroy
Population-Matched Transcriptome Prediction Increases Discovery And Replication Rate In Twas, Elyse Geoffroy
Master's Theses
Most genome-wide and transcriptome-wide association studies (GWAS, TWAS) focus on European populations; however, these results cannot always be accurately applied to non-European populations due to differences in genetic architecture. Using summary statistics from GWAS in the Population Architecture using Genomics and Epidemiology (PAGE) study, which comprises ~50,000 Hispanic/Latinos, African Americans, Asians, Native Hawaiians, and Native Americans, we perform transcriptome-wide association studies to determine gene-trait associations. Initially, we compared results using two transcriptome prediction models derived from the Multi-Ethnic Study of Atherosclerosis (MESA) populations: the African American (AFA) model and the Hispanic/Latino (HIS) model. We identified 141 unique genome-wide significant trait-associated …