Genetics
Driven by advances in array based and sequencing based technology, the Human Genome
Project, International HapMap Project, the 1,000 Genomes Project, and various forms
of genome-wide association studies, genetics is taking an ever-more-central role in
all the biomedical sciences. These advances have in turn resulted in an explosive
increase in the quantity and variety of genetic data. Faculty and students at U-M
Biostatistics play a leading role in a wide range of genetic studies, often in collaboration
with other investigators at the U-M Center for Statistical Genetics and around the
world. Specific studies seek to identify genetic variants and/or genes that play a
role in human diseases such as diabetes, asthma, psoriasis, cancer, bipolar disorder,
macular degeneration, that allow discrimination of different disease or tumor subtypes,
and that explore human genetic variation. Faculty and students also are working to
develop new statistical designs, analytic and computational methods, as well as integrative
tools, to ensure the efficient generation and use of genetic data from a wide range
of genetic studies, including genome-wide association studies, targeted, whole exome,
and whole genome sequencing studies, and expression studies. The statistical approaches
used in this area include likelihood-based and Bayesian methods, and often are computationally
intensive.
Faculty: G. Abecasis, V. Baladandayuthapani, M. Boehnke, L. Fritsche, H. Jiang, H.M. Kang, J. Kang, Y. Li, J. Morrison, B. Mukherjee, L. Scott, W. Wen, M. Zawistowski, X. Zhou
Links: U-M Center for Statistical Genetics, U-M Genome Science Training Program, U-M Biostatistical Training in Cancer Research, Rogel Cancer Center, U-M Department of Human Genetics, U-M Public Health Genetics Interdepartmental Concentration, Kidney Epidemiology & Cost Center