Studying population genetics and evolutionary theory, applied to human genetic variation

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

Locations of HGDP Eurasian populations and Native American populations from Wang et al. (2007, PLoS Genetics) that were analyzed by Ramachandran and Rosenberg (2011, AJPA). This comparative study of genetic differentiation on two continents showed that populations are more differentiated along the major axis of the Americas than along the major axis of Eurasia, perhaps due to the relative ease of migration east-west compared to migration north-south.

Figure 7 from Novembre and Ramachandran (2011, Ann Rev Genomics Hum Genet). A schematic of human demographic history, highlighting hypotheses investigated by recent single-nucleotide polymorphism studies discussed in the review. Designed by JN with input from SR.

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).

Celebrating Julia's transition to being a faculty member at Stanford (Summer 2016)!

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).