Hi, I'm Wes.

I'm a quantitative scientist
looking for my next research opportunity.

I am a quantitative scientist with a PhD in Bioinformatics and Computational Biology from UNC Chapel Hill. My experience is in the field of statistical genetics, and my research includes developing statistical approaches for genetic association and analyzing gene expression in model organisms. I have expertise in Bayesian nonparametric approaches, Bayesian model selection, and generalized linear models, with implementation in the R and Stan statistical computing languages.

I am interested in developing and applying cutting-edge methods to analyze large and complex biomedical datasets. I am currently seeking biomedical research and training opportunities involving machine learning, sparsity, causal inference, or other innovative statistical approaches.

Research

You can see my full list of publications on Google Scholar. Here are some of the projects I've been working on recently:

bmediatR

bmediatR is a Bayesian model selection approach for mediation analysis. It explores different causal relationships between a dependent variable (Y), an independent variable (X), and a potential mediator variable (M). Unlike the Sobel test, this approach distinguishes between partial and complete mediation, and it accommodates grouped predictors in X. Grouped predictors are useful for haplotype-based analyses and other cases when the independent variable is multidimensional, such as modeling multiple variants or non-additive effects. The manuscript for this approach is currently under development.

TIMBR

TIMBR is a Bayesian nonparametric approach for haplotype-based genetic association. It partitions haplotypes into a potentially smaller number of functional alleles with shared trait effects. This improves haplotype effect estimation and provides useful information about the number of causal variants at a quantitative trait locus. TIMBR partitions haplotypes using a Chinese restaurant process (CRP) and, by leveraging its relationship to the coalescent, generalizes the CRP to allow for tree-structured haplotype relatedness. The manuscript for this approach was highlighted in the December 2020 issue of Genetics.

Curriculum Vitae

Here's my CV.

I'm happy to provide additional details about my experience. References are available upon request.

Get in touch!

Have questions about my research or an exciting opportunity to share? You can send me an email, connect with me on LinkedIn, or direct message me on Twitter. I look forward to hearing from you!