Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


case1175867246.pdf (478.91 KB)

ETD Abstract Container

Abstract Header

STRATIFIED LINKAGE ANALYSIS BASED ON POPULATION SUBSTRUCTURE

Thompson, Cheryl L
http://rave.ohiolink.edu/etdc/view?acc_num=case1175867246

Abstract Details

2007, Doctor of Philosophy, Case Western Reserve University, Epidemiology and Biostatistics.
Genetic admixture and the resulting population stratification are known to increase the type I error rate in association studies. However, little work has been done to assess the impact of admixture and population stratification on linkage analysis. Genetic heterogeneity, where underlying genetic factors for disease differ between populations, has been demonstrated in many complex diseases. Currently, in an attempt to create more genetically homogeneous subpopulations, investigators often stratify their linkage analyses by race. However, self-reported race may not accurately reflect ethnicity and its use is controversial. Many algorithms exist for clustering individuals into more genetically homogeneous subpopulations. In this study, we propose the novel application of clustering algorithms to families in a linkage analysis dataset, and then use the inferred subpopulation as a stratifying variable to produce a potentially more informed, more powerful, and less controversial analysis. Linkage analysis stratified by population structure was applied to a sample of 229 African-American families with sarcoidosis on which a previous genome scan had been conducted. After applying a cluster analysis, the population was divided into two subpopulations. Evidence that some of the peaks found in the original scan were due to only one of the two subpopulations was found, with increases in significance for many of the linkage peaks. Additionally, a new peak only found in the smaller subpopulation was observed. To better understand and accurately interpret these results, we performed simulations and evaluated the type I error and power of a model-free sibling pair linkage method in a variety of scenarios representing possible characteristics of our sample and other admixed populations. The results of the simulations indicate that stratification on inferred subpopulation is an excellent way of reducing heterogeneity. This reduction in heterogeneity is apparent when there subpopulations are of relatively equal or quite different samples sizes. Results further indicate that stratification yields the most gain when assortive mating occurs, and when there are fewer subpopulations. As expected, this method does not work well in cases where the genetic susceptibility locus is the same for all subpopulations or where there the lack of distinct subpopulations makes stratification more difficult.
Courtney Gray-McGuire (Advisor)
147 p.
Linkage Analysis; admixture; population stratification; genetic heterogeneity

Recommended Citations

Citations

  • Thompson, C. L. (2007). STRATIFIED LINKAGE ANALYSIS BASED ON POPULATION SUBSTRUCTURE [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1175867246

    APA Style (7th edition)

  • Thompson, Cheryl. STRATIFIED LINKAGE ANALYSIS BASED ON POPULATION SUBSTRUCTURE. 2007. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1175867246.

    MLA Style (8th edition)

  • Thompson, Cheryl. "STRATIFIED LINKAGE ANALYSIS BASED ON POPULATION SUBSTRUCTURE." Doctoral dissertation, Case Western Reserve University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=case1175867246

    Chicago Manual of Style (17th edition)

case1175867246
588
© 2007, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.