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Statistics Colloquium
November 30 (Fri) 11 a.m.
Alavi Commons Room, 6625 Everett Tower
Matt Zawistowski
University of Michigan
The identification of genetic variants that contribute to complex disease is an area of intense interest in the field of human statistical genetics. Modern high-throughput sequencing technologies are revolutionizing our ability to study the genetic basis of disease by producing unprecedented quantities of molecular data. As a result, the challenge of complex disease genetics is shifting from acquiring suitably large genetic datasets to designing statistical methods to powerfully analyzing this data. Of particular interest are rare single nucleotide variants, inter-individual differences in DNA sequence that occur at very low frequency in the general population.
In this talk, I will provide an introduction to the field of statistical genetics and describe my particular research interests. I will present the Cumulative Minor Allele Test (CMAT), a powerful method for analyzing rare variants observed in case-control sequence data. The CMAT accumulates evidence of association across multiple rare variant sites within the same genic region using a simple and intuitive statistic based on extending standard single variant tests. I will then discuss study design considerations for analysis of sequence data including genotype imputation and population structure.