Courtney Rauchman

The Interplay of Linkage Disequilibrium Score Regression and Selection

The current method to estimate heritability based on genome-wide association studies (GWAS) summary statistics is to use Linkage Disequilibrium Score Regression (LDSC). Linkage Disequilibrium (LD) describes the association of genetic variants and LDSC makes use of the fact that variants which tag many other variants through high LD are more likely to tag a causal variant (Bulik-Sullivan et al. 2015). In fact, there is a linear relationship between the square of a variants normalized effect size and its LD score. Therefore, LDSC can be used to estimate both heritability and genetic correlations between traits by controlling for the effects of stratification in GWAS cohorts. A key assumption is that LDSC uses the independence of LD score and population differentiation. However, this assumption is violated when the model includes selection. This project aims to investigate the robustness of LDSC in scenarios involving varying types of selection, such as positive selection, background selection, and selective sweeps.

Message to Sponsor

I am beyond appreciative of The Rose Hills Foundation for allowing me to immerse myself in research for the entire summer with an incredible support system both inside and outside of the lab. The summer has strengthened my passion for the intersection of computation and genetics as well as reinforced my desire to attend graduate school and pursue a PhD in Bioinformatics. Following my experience as a SURF Rose Hills fellow, I feel more confident in my problem solving skills and my ability to effectively communicate my research to a broad audience. Overall, this summer has been pivotal to my research career and I could not be more grateful for the experience. Thank you, Rose Hills Foundation!
  • Major: Data Science
  • Sponsor: Rose Hills Experience
  • Mentor: Rasmus Nielsen