"Bottoms up: next generation analyses for high dimensional data"

Bottoms up: next generation analyses for high dimensional data”

Jacob Mayfield, Ph.D.
UMass
Wed, 10/29/2014 - 4:00pm

221 Integrated Sciences Building

High throughput data (-omics) produces huge lists of measurements for every sample. How can ten thousand rows turn into testable hypotheses? The familiar statistical methods that work well for single, known entities (supervised or top down analysis using T tests) are insufficient for discovering unknown patterns (unsupervised or bottom up analysis). I will discuss projects where contemporary statistics uncovered unexpected results, including a study of the human metabolic disease homocystinuria, a search for rare mutations using next generation sequencing, and the lipidomics of multidrug resistance in Mycobacterium tuberculosis.

Notes: 

Refreshments at 3:45pm