Statistics Seminar

“Overview of a Statistical Genetics and Genomics Research Program”
Dr. Alexander Lipka, University of Illinois, Urbana-Champaign

Date: Thursday, May 07, 2015
Time: 3:30 PM – 4:30 PM
Location: 165 Everitt
Sponsor: Department of Statistics, Dave Zhao

Abstract:
A statistical genetics and genomics research program should focus on developing new statistical approaches for analyzing genotypic and phenotypic data, establish interdisciplinary collaborations that increase our understanding of the genetic and genomic contributions to phenotypic variation, and provide mentoring opportunities for students and postdoctoral researchers. With this in mind, I review how I use my background in statistical genetics to develop statistical approaches for analyzing genotypic and phenotypic associations, and participate in interdisciplinary projects that focus on increasing the nutritional value of maize grain. Some specific topics discussed include the genome association and prediction integrated tool (GAPIT) R package, my role in developing analytical pipelines to identify loci associated with provitamin A and vitamin E content in maize grain, and the development of java plugins that use information criterion-based model selection. I then discuss some specific research topics I would like to investigate in the future, and highlight relevant collaboration opportunities.

http://illinois.edu/calendar/detail/1439?eventId=32183643&calMin=201505&cal=20150501&skinId=13335

“Recent Advances on Optimal Design of Experiments”
Dr. Min Yang, University of Illinois, Chicago

Date: Thursday, April 16, 2015
Time: 3:30 PM – 4:30 PM
Location: 160 English Building
NOTE: This is different than our usual location.
Sponsor: Department of Statistics, Annie Qu

Abstract:
Designing experiments is an integral part of the scientific process, both for discovery and verification. Resources are almost always scarce, and judicious use of the limited resources is essential. Identifying efficient and optimal designs for data collection is therefore paramount. In this talk, I will first give one simple example demonstrating the set up and the impact of efficient designs. Then I will review the classical tools of studying optimal designs. A new tool will be introduced. With this tool, many well-known results in the optimal design literature can be unified and extended. If time permitted, I plan to talk about a newly developed algorithm. The new algorithm can be applied to variety of optimality problems. More important it is much faster than the existing algorithms.

http://illinois.edu/calendar/detail/1439?eventId=32137177&calMin=201504&cal=20150413&skinId=13335

Statistics Seminar

“Prior-free Probabilistic Inference: Inferential Models”
Dr. Chuanhai Liu, Purdue University

Date: Thursday, March 12, 2015
Time: 3:30 PM – 4:30 PM
Location: 165 Everitt
Sponsor: Department of Statistics; Annie Qu, and Bo Li

Abstract: Developing solid foundations for scientific inference is the most fundamental but unsolved problem in statistics. We argue for two basic principles for truly prior-free probabilistic inference and introduce a new framework, which is built upon the two principles and called Inferential Models (IMs). It follows as a remark that IM bridges the gap between the Bayesian and frequentist schools of thought that has been previously considered impossible. In this talk, we introduce IMs with simple illustrative examples.

* This is joint work with Ryan Martin at UIC.

http://illinois.edu/calendar/detail/1439?eventId=32297522&calMin=201503&cal=20150309&skinId=1

Joint Mathematics and Statistics Colloquium

“The Yule-Coalescent Hierarchical Model”
Dr. James Degnan, University of New Mexico

Date: Tuesday, March 10, 2015
Time: 4:00 PM – 5:00 PM
Location: 165 Everitt
Sponsor: Departments of Mathematics and Statistics

Abstract:
Evolutionary biologists work with data at multiple levels which can be integrated into a hierarchical model: branching processes to model populations splitting (speciation), genes forming trees of ancestry within these populations, and mutations in genetic lineages.  Although much work has been done on each of these levels separately, there is much to understand regarding how the levels interact. By averaging effects at intermediate levels, we can study impacts of higher level processes, such as speciation and extinction rates, on lower levels, such as patterns in gene trees and DNA sequences, and in turn estimate parameters from higher levels using data collected at the lower levels.  In this talk I will examine some consequences of the Yule branching process model of speciation on distances between evolutionary trees and measures of tree balance.

http://illinois.edu/calendar/detail/1439?eventId=32516970&calMin=201503&cal=20150305&skinId=1