Andrew Bass

Andy’s methodological work addresses how to extract reliable signal from genome-wide data. In particular, he has developed frameworks that exploit pleiotropy to improve variant discovery, detect latent genetic interactions across multiple traits, analyze differential co-expression for general risk factors, and improve discovery in gene expression studies. He earned his PhD in quantitative and computational biology at Princeton University and has held postdoctoral posts at Emory University and the University of Cambridge. A consistent thread throughout is releasing his methods as maintained open-source software: he created the R packages sffdr, lit, kdca, and superSeq and maintains the widely used packages qvalue and edge.