Abstract

This revised project is concerned with developing new statistical methodology for population genetic data. Attention will be focused on three main areas: the characterization of population structure, the characterization of the association patterns within and between genetic markers and along haplotypes, and the characterization of the identity status of sets of more than two alleles. Theory will be developed at least in part in response to the needs of current large-scale SNP surveys of humans and other species. ? ? Specific topics include determining the sampling properties of population-specific measures of population structure and the comparison of marker- and trait-based estimates of population structure. A comparison will be conducted of current methods for defining haplotype blocks, and consideration of alternative methods based on diversity or on contingency-table and regression analyses of one marker versus haplotypes of subsequent markers. The means for drawing inferences about associations among more than two alleles at one locus, or among single alleles taken from multiple loci will be developed. ? ? ?

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM075091-01A1
Application #
7091719
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Eckstrand, Irene A
Project Start
2006-05-01
Project End
2010-04-30
Budget Start
2006-05-01
Budget End
2007-04-30
Support Year
1
Fiscal Year
2006
Total Cost
$291,095
Indirect Cost

  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

Xue, Angli; Wu, Yang; Zhu, Zhihong et al. (2018) Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nat Commun 9:2941
Graffelman, Jan; Weir, Bruce S (2018) Multi-allelic exact tests for Hardy-Weinberg equilibrium that account for gender. Mol Ecol Resour 18:461-473
Goudet, Jérôme; Kay, Tomas; Weir, Bruce S (2018) How to estimate kinship. Mol Ecol 27:4121-4135
Qi, Ting; Wu, Yang; Zeng, Jian et al. (2018) Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood. Nat Commun 9:2282
Graffelman, Jan; Weir, Bruce S (2018) On the testing of Hardy-Weinberg proportions and equality of allele frequencies in males and females at biallelic genetic markers. Genet Epidemiol 42:34-48
Yengo, Loic; Zhu, Zhihong; Wray, Naomi R et al. (2018) Reply to Kardos et al.: Estimation of inbreeding depression from SNP data. Proc Natl Acad Sci U S A 115:E2494-E2495
Zheng, Xiuwen; Gogarten, Stephanie M; Lawrence, Michael et al. (2017) SeqArray-a storage-efficient high-performance data format for WGS variant calls. Bioinformatics 33:2251-2257
Galván-Femenía, Iván; Graffelman, Jan; Barceló-I-Vidal, Carles (2017) Graphics for relatedness research. Mol Ecol Resour 17:1271-1282
Puig, X; Ginebra, J; Graffelman, J (2017) A Bayesian test for Hardy-Weinberg equilibrium of biallelic X-chromosomal markers. Heredity (Edinb) 119:226-236
Graffelman, Jan; Jain, Deepti; Weir, Bruce (2017) A genome-wide study of Hardy-Weinberg equilibrium with next generation sequence data. Hum Genet 136:727-741

Showing the most recent 10 out of 75 publications