Metsky HC, Matranga CB, Wohl S, Schaffner SF, et al. Zika virus evolution and spread in the Americas. Nature. 2017;546:411-415.
Daniels RF, Schaffner SF, Wenger EA, Proctor JL, et al. Modeling malaria genomics reveals transmission decline and rebound in Senegal. Proc Natl Acad Sci U S A. 2015;112(22):7067-7072.
Zuk O, Schaffner SF, Samocha K, Do R, et al. Searching for missing heritability: designing rare variant association studies. Proc Natl Acad Sci U S A. 2014;111(4):E455-E464.
Stephen Schaffner, Ph.D.
Stephen Schaffner is a senior computational biologist in the Infectious Disease and Microbiome Program of the Broad Institute of MIT and Harvard, where he uses the tools of population genetics to study human genetics and infectious disease, including viral, malaria, and host genetics. Schaffner has developed techniques for detecting the effects of positive selection on genetic variation, carried out model-based studies of human demographic history, and developed tools for identifying recent common ancestry in malaria parasites. He often focuses on detecting cases of positive natural selection, where a given trait is beneficial for the organism and is therefore selected for in the population.
Schaffner performs computer simulations of genetic variation and studies the history of human demographics. He also works to understand linkage disequilibrium, a term used in the field of population genetics to describe a combination of genetic markers that occurs more or less often than expected. These studies can aid the search for genetic markers linked to traits or disease.
Schaffner joined the Whitehead Institute in 1999 and moved to the Broad Institute upon its launch in 2004. He holds a Ph.D. in experimental particle physics from Yale University.
Contact Stephen Schaffner via email at firstname.lastname@example.org.