A new statistical tool developed at University of Chicago makes it quicker and easier to find genetic variants underlying disease. The tool, described in a paper today in Nature Genetics, combines data from genome wide association studies (GWAS) and predictions of genetic expression to better identify disease-causal variants. Causal-transcriptome-wide association studies (cTWAS) uses a Bayesian […]
