Abstract

The statistical genetics faculty at the University of Washington propose renewal of the predoctoral training program in biostatistics that emphasizes applications to genetics. The faculty members belong to the very strong departments of Biostatistics, Genome Sciences or Statistics at the University of Washington. The trainees will pursue Ph.D. degrees in one of the three departments. The training program will include the current Ph.D. tracks in statistical genetics offered by the Departments of Biostatistics and Statistics but it will have the additional feature of rotations in experimental laboratories and opportunities for internships in local companies. In addition to formal courses taught by international experts in statistical genetics, the training program features journal club, seminars and retreats. Trainees will also be able to attend modules in the annual Summer Institute in Statistical Genetics held at the University of Washington.

Public Health Relevance

Biology in general and genetics in particular, is becoming increasingly quantitative. Many major advances in medical science are being made possible by the massive amounts of data from the Human Genome Project, the HapMap project, the 1000 Genomes project and related activities. Managing and interpreting these data requires the development and application of new statistical methodologies. This training grant will support highly talented students in the Departments of Biostatistics, Genome Sciences or Statistics and ensure that they are trained to lead such development and application.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Institutional National Research Service Award (T32)
Project #
5T32GM081062-07
Application #
8501531
Study Section
National Institute of General Medical Sciences Initial Review Group (BRT)
Program Officer
Brazhnik, Paul
Project Start
2007-07-01
Project End
2017-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
7
Fiscal Year
2013
Total Cost
$157,358
Indirect Cost
$8,490

  Institution

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

  Publications

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
Valcarcel, Alessandra; Grinde, Kelsey; Cook, Kaitlyn et al. (2016) A multistep approach to single nucleotide polymorphism-set analysis: an evaluation of power and type I error of gene-based tests of association after pathway-based association tests. BMC Proc 10:349-355
Chen, Han; Wang, Chaolong; Conomos, Matthew P et al. (2016) Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models. Am J Hum Genet 98:653-66
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

Showing the most recent 10 out of 23 publications