The University of Washington (UW) is a leader in biostatistics, genome sciences, public health genet- ics and statistics, conducting world-class biomedical research. Recent technological advancements have facilitated a new era of biomedical research in genomics. Genetic researchers now have ac- cess to whole-genome and whole-exome sequence data for humans and other organisms, as well as other high-dimensional genomic data. There is great potential for these data to provide unprece- dented insight into the genetic underpinnings of human health and complex diseases, and new statistical and computational methods must be developed to effectively analyze and interpret these data. There is a dearth, however, of biomedical researchers who are equipped with the necessary statistical training to lead such development and application. There is a critical need to increase the number of scientists in the biomedical research community who have both a strong foundation in biostatistics/statistics and interdisciplinary training in genetics. The statistical genetics faculty at the University of Washington propose renewal of the very suc- cessful Predoctoral Training in Statistical Genetics Program (STATGEN) at the University of Wash- ington. This STATGEN program is currently in its second ?ve-year award period, and the primary goal of the program is to train a new generation of scientists who have expertise in statistical ge- netics and are equipped with the necessary skills to work at the interface of statistics and genetics for biomedical research of today and the future. The program will draw six predoctoral trainees from PhD programs in Biostatistics, Genome Sciences, Statistics, and the Institute for Public Health at UW. Trainees take a rigorous curriculum that includes three courses in statistical genetics and two courses in genomics. Each trainee is paired with a world-class faculty mentor in the program and conducts research in statistical genetics under the supervision of the mentor. Other prominent fea- tures of the STATGEN program include a statistical genetics seminar, journal clubs, formal research presentations by trainees, rotations in laboratories of faculty mentors in the program, opportunities to attend summer courses taught by world-renowned and international experts in the annual Sum- mer Institute in Statistical Genetics (SISG) and Summer Institute in Statistics for Big Data (SISBID) held at annually at UW, and summer research opportunities. Predoctoral trainees who complete the STAGEN Program will be equipped with the knowledge and skills in the development and application of statistical methodologies that are essential for cutting-edge biomedical research in genetics.

Public Health Relevance

Technological advancements in genomics have lead to a wealth of data, facilitating a fundamental change in the landscape of biomedical research. New statistical and computational methods, how- ever, must be developed to effectively analyze and interpret these data, and a new generation of scientists who have a strong foundation in statistics as well as interdisciplinary training in genetics is urgently needed. The proposed program will provide interdisciplinary training in statistics and genet- ics for highly talented predoctoral students in the Departments of Biostatistics, Genome Sciences, Statistics, and the Institute for Public Health Genetics at the University of Washington to ensure that they have the necessary knowledge and skills for cutting-edge biomedical genetic research.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Institutional National Research Service Award (T32)
Project #
5T32GM081062-13
Application #
9722276
Study Section
NIGMS Initial Review Group (TWD)
Program Officer
Gibbs, Kenneth D
Project Start
2007-07-01
Project End
2022-06-30
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
13
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Washington
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Grinde, Kelsey E; Arbet, Jaron; Green, Alden et al. (2017) Illustrating, Quantifying, and Correcting for Bias in Post-hoc Analysis of Gene-Based Rare Variant Tests of Association. Front Genet 8:117
Hodonsky, Chani J; Jain, Deepti; Schick, Ursula M et al. (2017) Genome-wide association study of red blood cell traits in Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos. PLoS Genet 13:e1006760
Jain, Deepti; Hodonsky, Chani J; Schick, Ursula M et al. (2017) Genome-wide association of white blood cell counts in Hispanic/Latino Americans: the Hispanic Community Health Study/Study of Latinos. Hum Mol Genet 26:1193-1204
Morrison, Jean; Laurie, Cathy C; Marazita, Mary L et al. (2016) Genome-wide association study of dental caries in the Hispanic Communities Health Study/Study of Latinos (HCHS/SOL). Hum Mol Genet 25:807-16
Green, Alden; Cook, Kaitlyn; Grinde, Kelsey et al. (2016) A general method for combining different family-based rare-variant tests of association to improve power and robustness of a wide range of genetic architectures. BMC Proc 10:165-170
Popejoy, Alice B; Fullerton, Stephanie M (2016) Genomics is failing on diversity. Nature 538:161-164
Conomos, Matthew P; Reiner, Alexander P; Weir, Bruce S et al. (2016) Model-free Estimation of Recent Genetic Relatedness. Am J Hum Genet 98:127-48
Baraff, Aaron J; McCormick, Tyler H; Raftery, Adrian E (2016) Estimating uncertainty in respondent-driven sampling using a tree bootstrap method. Proc Natl Acad Sci U S A 113:14668-14673
Browning, Sharon R; Grinde, Kelsey; Plantinga, Anna et al. (2016) Local Ancestry Inference in a Large US-Based Hispanic/Latino Study: Hispanic Community Health Study/Study of Latinos (HCHS/SOL). G3 (Bethesda) 6:1525-34
Greco, Brian; Hainline, Allison; Arbet, Jaron et al. (2016) A general approach for combining diverse rare variant association tests provides improved robustness across a wider range of genetic architectures. Eur J Hum Genet 24:767-73

Showing the most recent 10 out of 23 publications