UCSF

This work revolves around developing, applying, and evaluating computational methods for the analysis of genomic datasets of recently admixed populations. Individuals from recently admixed populations, such as African Americans and Hispanic Latinos, derive their genomes from multiple genetically distinct ancestral populations. For example, African Americans have locus-specific ancestry from African and European genomes, which reflects demographic history and influences disease predisposition. Genomic studies of admixed populations therefore provide an enormous opportunity to investigate the influence of genetic variation on human phenotypic diversity. Furthermore, such studies offer a framework to test the generalizability of findings on genotype-phenotype relationships originally obtained in more homogeneous populations (i.e. Europeans), potentially yielding insights into underlying mechanisms. Here we present four novel statistical/computational approaches that leverage the unique genetic makeup of admixed populations to aid in deepening our understanding of the effect of human genetic variation on the phenome.