DEPARTMENT OF STATISTICS
Statistics Colloquium
University of Connecticut
Storrs, Connecticut
The Department of Statistics Cordially invites you to a Colloquium
Yi-Hui Zhou
Department of Biostatistics
University of North Carolina, Chapel Hill
Another look at statistical testing and integrative analysis
in a big (ger) data era
ABSTRACT
Nearly 20 years after the introduction of microarrays, and 13 years after the draft sequencing of the human genome, basic statistical issues of multiple testing remain important for discovery-based and translational science. At the extreme testing thresholds required for many -omics platforms, standard testing approaches can have highly inflated false positive rates, leading to false discoveries. Another problem, not always recognized by practitioners, is that standard approaches to analyses of “pathways” can also lead to numerous false discoveries. Permutation analysis provides a rigorous framework for testing, but is computationally intensive and cumbersome. In this talk, I will introduce the basic rationale for multiple testing and permutation analysis when dealing with high-dimensional data. For testing individual features in ‘omics platforms, I will describe the Moment-Corrected Correlation (MCC) approach to perform extremely fast and accurate testing. For testing pathways, or other defined grouped sets of features, I will introduce safeExpress, a new approach to perform highly rigorous pathway testing. The combination of these two methods, along with extensions for handling family members and covariates, lays the groundwork for a new comprehensive approach to handle the next generation of 'omics data. Finally, I will describe several additional projects and software tools that are applying ideas from MCC and safeExpress to association, eQTL, and and RNA-Seq datasets.
DATE: Wednesday, February 5, 2014
TIME: 4:00 p.m.
PLACE: Philip E. Austin Building – Room 344
Coffee will be served at 3:30 in AUST 326
For more information, contact: Tracy Burke at 860-486-3413