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Full-Text Articles in Life Sciences
Multivariate Adaptive Shrinkage Improves Cross-Population Transcriptome Prediction And Association Studies In Underrepresented Populations, Daniel Araujo, Chris Nguyen, Xiaowei Hu, Anna V. Mikhaylova, Christopher R. Gignoux, Kristin Ardlie, Kent D. Taylor, Peter Durda, Yongmei Liu, George Papanicolaou, Michael H. Cho, Stephen S. Rich, Jerome I. Rotter, Nhlbi Topmed Consortium, Hae Kyung Im, Ani Manichaikul, Heather Wheeler
Multivariate Adaptive Shrinkage Improves Cross-Population Transcriptome Prediction And Association Studies In Underrepresented Populations, Daniel Araujo, Chris Nguyen, Xiaowei Hu, Anna V. Mikhaylova, Christopher R. Gignoux, Kristin Ardlie, Kent D. Taylor, Peter Durda, Yongmei Liu, George Papanicolaou, Michael H. Cho, Stephen S. Rich, Jerome I. Rotter, Nhlbi Topmed Consortium, Hae Kyung Im, Ani Manichaikul, Heather Wheeler
Biology: Faculty Publications and Other Works
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 that methods that leverage shared regulatory effects across different conditions, in this case, across different populations, may improve cross-population transcriptome prediction. To test this hypothesis, we made transcriptome prediction models for use in transcriptome-wide association studies (TWASs) using different methods (elastic net, joint-tissue imputation [JTI], matrix expression quantitative trait loci [Matrix eQTL], multivariate adaptive shrinkage in R [MASHR], and transcriptome-integrated genetic association resource [TIGAR]) and tested their out-of-sample transcriptome prediction accuracy …
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 …
Gene-Based Association Study For Lipid Traits In Diverse Cohorts Implicates Bace1 And Sidt2 Regulation In Triglyceride Levels, Angela Andaleon, Lauren S. Mogil, Heather Wheeler
Gene-Based Association Study For Lipid Traits In Diverse Cohorts Implicates Bace1 And Sidt2 Regulation In Triglyceride Levels, Angela Andaleon, Lauren S. Mogil, Heather Wheeler
Bioinformatics Faculty Publications
Plasma lipid levels are risk factors for cardiovascular disease, a leading cause of death worldwide. While many studies have been conducted on lipid genetics, they mainly focus on Europeans and thus their transferability to diverse populations is unclear. We performed SNP- and gene-level genome-wide association studies (GWAS) of four lipid traits in cohorts from Nigeria and the Philippines and compared them to the results of larger, predominantly European meta-analyses. Two previously implicated loci met genome-wide significance in our SNP-level GWAS in the Nigerian cohort, rs34065661 in CETP associated with HDL cholesterol (P = 9.0 × 10−10) and …
Genetic And Transcriptional Analysis Of Human Host Response To Healthy Gut Microbiota, Michael B. Burns, Allison L. Richards, Adnan Alazizi, Luis B. Barreiro, Roger Pique-Regi, Ran Blekhman, Francesca Luca
Genetic And Transcriptional Analysis Of Human Host Response To Healthy Gut Microbiota, Michael B. Burns, Allison L. Richards, Adnan Alazizi, Luis B. Barreiro, Roger Pique-Regi, Ran Blekhman, Francesca Luca
Biology: Faculty Publications and Other Works
Many studies have demonstrated the importance of the gut microbiota in healthy and disease states. However, establishing the causality of host-microbiota interactions in humans is still challenging. Here, we describe a novel experimental system to define the transcriptional response induced by the microbiota for human cells and to shed light on the molecular mechanisms underlying host-gut microbiota interactions. In primary human colonic epithelial cells, we identified over 6,000 genes whose expression changed at various time points following coculturing with the gut microbiota of a healthy individual. Among the differentially expressed genes we found a 1.8-fold enrichment of genes associated with …
Assessment Of A Metaviromic Dataset Generated From Nearshore Lake Michigan, Siobhan C. Watkins, Neil Kuehnle, C Anthony Ruggeri, Kema Malki, Katherine Bruder, Jinan Elayyan, Kristina Damisch, Naushin Vahora, Paul O'Malley, Brianne Ruggles-Sage, Zachary Romer, Catherine Putonti
Assessment Of A Metaviromic Dataset Generated From Nearshore Lake Michigan, Siobhan C. Watkins, Neil Kuehnle, C Anthony Ruggeri, Kema Malki, Katherine Bruder, Jinan Elayyan, Kristina Damisch, Naushin Vahora, Paul O'Malley, Brianne Ruggles-Sage, Zachary Romer, Catherine Putonti
Bioinformatics Faculty Publications
Bacteriophages are powerful ecosystem engineers. They drive bacterial mortality rates and genetic diversity, and affect microbially mediated biogeochemical processes on a global scale. This has been demonstrated in marine environments; however, phage communities have been less studied in freshwaters, despite representing a potentially more diverse environment. Lake Michigan is one of the largest bodies of freshwater on the planet, yet to date the diversity of its phages has yet to be examined. Here, we present a composite survey of viral ecology in the nearshore waters of Lake Michigan. Sequence analysis was performed using a web server previously used to analyse …