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Population Structure in the Cincinnati area

Baric, Michelle B

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2013, MS, University of Cincinnati, Medicine: Genetic Counseling.
Background: Population studies from a single study site may result in unexpected substructure, especially in the United States, where admixture is common. Thus it is important to examine the population substructure of US cities to better understand potential biases for genetic studies. This study examines the continental structure and substructure of the greater Cincinnati area. Methods: Study subjects included self-reported white/Caucasian and black/African American participants in the Cincinnati Genomic Control Cohort (GCC). Principal component analyses (PCA) and Eigensoft were used to analyze the data, chromosome by chromosome, to determine if we could separate both population groups and assess the level of agreement between self-reported and genetic race. Additionally, within the self-reported white cohort, population substructure was evaluated using markers from several chromosomes at varying allele frequencies (0-5%, 6-20%, and 21% +) and three sets of ancestry informative markers (AIMs). Results: Clear continental structure was observed when comparing self-reported white and black populations. The overall rate of agreement between self-reported and genetic race was 99% (981/983). There was no substructure identified in the self-reported white population when using three different sets of AIMs however distinct clusters were present when using rare, medium, and common alleles. Moreover, different chromosomes produced different clustering patterns, when examined at the same allele frequency. Conclusions: Self-reported race is a good tool for determining continental ancestry; however self-reported race may not be sufficient when trying to achieve homogenous cases and controls. Specifically, if identified substructure differs based on the variants selected, it will be important to ensure that a robust set of variants are selected, that reflect variation across the genome, to detect potential population stratification. If variation is not accounted for, bias may be introduced into studies leading to false positive results.
Mehdi Keddache, Ph.D. (Committee Chair)
Cynthia Prows (Committee Member)
Lisa Martin, Ph.D. (Committee Member)
40 p.

Recommended Citations

Citations

  • Baric, M. B. (2013). Population Structure in the Cincinnati area [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1367945142

    APA Style (7th edition)

  • Baric, Michelle. Population Structure in the Cincinnati area. 2013. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1367945142.

    MLA Style (8th edition)

  • Baric, Michelle. "Population Structure in the Cincinnati area." Master's thesis, University of Cincinnati, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1367945142

    Chicago Manual of Style (17th edition)