Dr. Emile Chimusa (Bioinformatics Consultant)

Dr. Chimusa is a statistical geneticist, his expertise is in population structure and genome wide patterns of variation within and between species to address fundamental questions in biology, anthropology, and medicine. He holds a Ph.D. in Computational Biology and Bioinformatics, and has extensive experience in designing and applying statistical methods to large genomics data sets in computational biology and statistical genetics. He became a faculty member at the University of Cape Town (UCT) in 2014, and currently holds a senior lectureship position at the Division of Human Genetics, Department of Pathology, UCT.

Dr. Chimusa had led several projects including (1) a post GWAS method, ancGWAS, an algebraic graph-based approach to deconvolute the interactions between genes and identify significant disease sub-networks underlying the pathogenesis of complex diseases (Chimusa et al., 2016 Bioinformatics); (2) A study of genome-wide, dense SNP (~900K) and copy number polymorphism data of indigenous southern Africans, addressing a strategy to identify the signature of selection in admixed populations (Chimusa et al., 2015 PLoS Genet); (3) PROXYANC, an optimal quadratic programming approach to select the best proxy ancestral populations of multi-way admixed populations and to examine the fine genetic characterization of ancestral components in multi-way admixed populations (Chimusa et al., 2013 PLos One).