Abstract

The objectives of this research are to address some statistical issues related to association mapping (or disequilibrium mapping) for complex traits. We plan to develop robust, yet efficient statistical methods to deal with some important problems that have not been addressed or have not been fully resolved in the literature.
The specific aims are: ? ? 1. To develop simple and robust techniques for assessing population stratification when anonymous markers are available, but are not necessarily in linkage equilibrium with each other. ? ? 2. To develop an efficient method for capturing the simultaneous effects of multiple genetic variants that individually make only a small contribution to the total disease risk, while controlling the overall false positive rate. ? ? 3. To explore robust non-parametric methods for estimating and assessing haplotypes associated with disease: mapping disease-associated haplotypes without pre-assigning window size of the haplotype; mapping multiple pre-disposing haplotypes; and mapping when haplotypes cannot be discerned unambiguously. ? ? Software to carry out the specific aims will be developed and implemented in the R or C computing environment for public distribution. ? ?

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM074175-02
Application #
7212146
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Anderson, Richard A
Project Start
2006-04-01
Project End
2010-03-31
Budget Start
2007-04-01
Budget End
2008-03-31
Support Year
2
Fiscal Year
2007
Total Cost
$198,472
Indirect Cost

  Institution

Name
University of North Carolina Chapel Hill
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599

  Publications

Lu, Zhao-Hua; Zhu, Hongtu; Knickmeyer, Rebecca C et al. (2015) Multiple SNP Set Analysis for Genome-Wide Association Studies Through Bayesian Latent Variable Selection. Genet Epidemiol 39:664-77
Crowley, James J; Zhabotynsky, Vasyl; Sun, Wei et al. (2015) Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance. Nat Genet 47:353-60
Yin, Zhaoyu; Xia, Kai; Chung, Wonil et al. (2015) Fast eQTL Analysis for Twin Studies. Genet Epidemiol 39:357-65
Sun, Wei; Liu, Yufeng; Crowley, James J et al. (2015) IsoDOT Detects Differential RNA-isoform Expression/Usage with respect to a Categorical or Continuous Covariate with High Sensitivity and Specificity. J Am Stat Assoc 110:975-986
Wright, Fred A; Sullivan, Patrick F; Brooks, Andrew I et al. (2014) Heritability and genomics of gene expression in peripheral blood. Nat Genet 46:430-7
Zou, Fei; Sun, Wei; Crowley, James J et al. (2014) A novel statistical approach for jointly analyzing RNA-Seq data from F1 reciprocal crosses and inbred lines. Genetics 197:389-99
Rashid, Naim U; Sun, Wei; Ibrahim, Joseph G (2014) Some Statistical Strategies for DAE-seq Data Analysis: Variable Selection and Modeling Dependencies among Observations. J Am Stat Assoc 109:78-94
Xia, Kai; Yu, Yang; Ahn, Mihye et al. (2014) Environmental and genetic contributors to salivary testosterone levels in infants. Front Endocrinol (Lausanne) 5:187
Ha, Min Jin; Sun, Wei (2014) Partial correlation matrix estimation using ridge penalty followed by thresholding and re-estimation. Biometrics 70:765-73
Chung, Wonil; Zou, Fei (2014) Mixed-effects models for GAW18 longitudinal blood pressure data. BMC Proc 8:S87

Showing the most recent 10 out of 41 publications