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Biostatistics Seminars

Department of Biostatistics Seminar Series

The Department of Biostatistics presents a regular speaker series each semester, generally on Thursday afternoon each week. Diverse experts lecture on their work in biostatistics.

Upcoming Biostats Seminars

Thu 9/20/2018 3:30PM - 4:30PM
Biostatistics at the FDA - Jessica (Jeongsook) Kim, FDA
Public Health Auditorium (G23)

Jessica Kim, Lead Mathematical Statistician, Food and Drug Administration, will present, “Biostatistics at the FDA”.
Thu 9/27/2018 3:30PM - 4:30PM
Hyun Jung (HJ) Park, University of Pittsburgh
Public Health Auditorium (G23)

Hyun Jung (HJ) Park, Department of Human Genetics, University of Pittsburgh, will present, “Insights into RNA Biology from Statistical Modeling for CancerTherapeutics”.
Thu 10/4/2018 3:30PM - 4:30PM
Peter X.K. Song, University of Michigan
Public Health Auditorium (G23)

Peter X.K. Song, Department of Biostatistics, University of Michigan, will present, “HASS: Hybrid Algorithm for Subgroup Search via ADMM and EM Algorithms”.
Thu 10/25/2018 3:30PM - 4:30PM
Dana L. Tudorascu, University of Pittsburgh
Public Health Auditorium (G23)

Thu 11/1/2018 3:30PM - 4:30PM
Jingyi (Jessica) Li, University of California, Los Angeles
Public Health Auditorium (G23)

Thu 11/8/2018 3:30PM - 4:30PM
Hongzhe Li (Lee), University of Pennsylvania
Public Health Auditorium (G23)

Thu 11/29/2018 3:30PM - 4:30PM
Dulal K. Bhaumik, University of Illinois at Chicago
Public Health Auditorium (G23)

Previous Biostats Seminars

Biostatistics Seminar Series

David Gerard, University of Chicago

Thursday 1/25 3:30PM - 4:30PM
Public Health Auditorium (G23)

Biostatistics guest speaker, David Gerard, University of Chicago, will present, " Better Genotyping for Polyploids."

Modern genomics has revolutionized how we answer questions about evolution, population dynamics, medicine, and plant and animal breeding. To answer these questions, we must first be able to detect and quantify (or "genotype") differences in individual genomes. Many scientists have used next generation sequencing technologies to genotype diploid individuals (those with two copies of their genomes). However, methods to genotype polyploids (those with morethan two copies of their genomes) are just emerging. We present two main contributions: (i) many datasets feature related individuals, and so we use the structure of Mendelian segregation to borrow strength between polyploid siblings to improve genotyping; (ii) we additionally draw attention to and then model common aspects of next generation sequencing data: sequencing error, allele bias, overdispersion, and outlying observations. We apply our method to a dataset of hexaploid sweet potatoes and discuss future extensions.

Last Updated On Friday, January 12, 2018 by Kapko, Bernadette E
Created On Friday, January 05, 2018


For information on seminars and events in the department, contact:

Bernadette Kapko

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