Harvard School of Public Health, Departments of Epidemiology and Biostatistics
Broad Institute of MIT and Harvard, Program in Medical and Population Genetics
Alkes L. Price is an Assistant Professor in the Departments of Epidemiology and Biostatistics at the Harvard School of Public Health. His research focuses on the development of statistical methods for uncovering the genetic basis of human disease, and on the population genetics underlying these methods. Methods and software that he has developed include PCA-based inference of genome-wide ancestry and correction for population stratification (EIGENSTRAT), inference of local ancestry in admixed populations (HAPMIX), joint SNP and admixture association mapping (MIXSCORE), and informed conditioning on clinical covariates in case-control studies (LTSCORE).
Department of Genetics
Stanford University School of Medicine
I am a Medical Doctor by training and have a strong interest in understanding patterns of human genetic variation and its implications in health and disease, evolution, and population history reconstruction. After graduating from the University of Guadalajara School of Medicine in 2002, I moved from Mexico to Barcelona, Spain to pursue a PhD in Evolutionary Biology and Population Genetics, which I received from the Pompeu Fabra University in 2009.
I joined the Bustamante Lab at Stanford University in January 2010, where I got the opportunity to focus my research on population genomics in the Americas. My current work involves the use of genome-wide data sets to study fine-scale patterns of population structure in both Native Americans and Hispanic/Latino populations from throughout the Americas. One of the major goals is to better understand the evolutionary processes, including natural selection, that have shaped Native American genomes during the last ~10,000 years of independent evolution since the peopling of the Americas and before the European contact.
The other major goal is aimed at understanding the dynamics of the admixture process in present day Hispanic/Latino populations since the European contact. By applying methods of local ancestry estimation we are trying to trace back ancestry-specific segments of the genome to their potential source populations at the sub-continental level. Defining patterns of local variation and sub-continental ancestry in admixed populations and individual genomes is also allowing the field to move towards a more personalized view of medical genomics and to promote the study of diverse populations underrepresented in current catalogs of human variation.
Personal website: http://www.stanford.edu/~morenoe/
Bustamante Lab: med.stanford.edu/bustamantelab/research/popgenomicsA.html
Analytic and Translational Genetics Unit, MGH Simches Research Center, Boston, MA, USA
Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
Stephan is a key member of the Psychiatric GWAS Consortium (PGC), a collaborative effort that involves 70 GWAS datasets from research groups from 17 countries. Stephan is responsible for performing the combined analysis of the raw genetic data from the Consortium members. To do this, he has created a computer pipeline that standardizes data, imputes missing values, performs the final analysis and brings the results into displayable format (e.g. the Web based tool RICOPILI). This collection of computer programs is unique in its ability to analyze millions and millions of data points in a short period of time, a critical ability that has allowed genome-wide association studies of psychiatric data to produce concrete results. Stephan’s current GWAS research focuses on schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, attention deficit hyperactivity disorder, and cross-disease analyses. In addition to this research project, Stephan is collaborating with a plethora of additional GWAS groups (mostly consortias) for human traits, like HIV, Crohn’s Disease, AMD (age-related macular degeneration), Psychopharmacogenetics, smoking, height, weight, sudden cardiac death, stroke, anxiety, multiple sclerosis, and restless legs syndrome.