Determining the causes and consequences of human genetic variation,
using population genetics, statistics, and evolutionary theory

2017 Holiday Hackathon (in Back Bay, Boston) to celebrate the end of a great year!


A meta-selfie outside our current home, Watson CIT at Brown


Our Spring 2018 inaugural lab potluck (cookbook forthcoming).


The Ramachandran Lab wins the 2016 EEB prize for Best Halloweeb Costume! L to R: Anger, Sadness, Disgust.


Former postdoc Julia Palacios speaking about her paper on Bayesian inference of population size changes from sequential genealogies to the Boston Evolution Supergroup in June 2015 (SR also spoke).


Postdoc Lauren Sugden at the poster session during Probabilistic Modeling in Genomics (CSHL, 2015).



Research in the Ramachandran lab addresses problems in population genetics and evolutionary theory, generally using humans as a study system. Our work uses mathematical modeling, applied statistical methods, and computer simulations to make inferences from genetic data. We answer questions like: what loci are under strong adaptive selection in the human genome? are there genetic pathways we can identify that underlie common diseases such as diabetes? does genetic variation account for some ethnic disparities in disease incidence and outcome? what features of human demographic history can we infer from genetic data alone?

We are currently funded by grants from the National Science Foundation (NSF CAREER DBI-1452622) and the National Institutes of Health (R01GM118652 and COBRE award P20GM109035).