The Population Reference Sample, POPRES: a resource for population, disease, and pharmacological genetics research - PubMed (original) (raw)

doi: 10.1016/j.ajhg.2008.08.005. Epub 2008 Aug 28.

Katarzyna Bryc, Karen S King, Amit Indap, Adam R Boyko, John Novembre, Linda P Briley, Yuka Maruyama, Dawn M Waterworth, Gérard Waeber, Peter Vollenweider, Jorge R Oksenberg, Stephen L Hauser, Heide A Stirnadel, Jaspal S Kooner, John C Chambers, Brendan Jones, Vincent Mooser, Carlos D Bustamante, Allen D Roses, Daniel K Burns, Margaret G Ehm, Eric H Lai

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The Population Reference Sample, POPRES: a resource for population, disease, and pharmacological genetics research

Matthew R Nelson et al. Am J Hum Genet. 2008 Sep.

Abstract

Technological and scientific advances, stemming in large part from the Human Genome and HapMap projects, have made large-scale, genome-wide investigations feasible and cost effective. These advances have the potential to dramatically impact drug discovery and development by identifying genetic factors that contribute to variation in disease risk as well as drug pharmacokinetics, treatment efficacy, and adverse drug reactions. In spite of the technological advancements, successful application in biomedical research would be limited without access to suitable sample collections. To facilitate exploratory genetics research, we have assembled a DNA resource from a large number of subjects participating in multiple studies throughout the world. This growing resource was initially genotyped with a commercially available genome-wide 500,000 single-nucleotide polymorphism panel. This project includes nearly 6,000 subjects of African-American, East Asian, South Asian, Mexican, and European origin. Seven informative axes of variation identified via principal-component analysis (PCA) of these data confirm the overall integrity of the data and highlight important features of the genetic structure of diverse populations. The potential value of such extensively genotyped collections is illustrated by selection of genetically matched population controls in a genome-wide analysis of abacavir-associated hypersensitivity reaction. We find that matching based on country of origin, identity-by-state distance, and multidimensional PCA do similarly well to control the type I error rate. The genotype and demographic data from this reference sample are freely available through the NCBI database of Genotypes and Phenotypes (dbGaP).

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Figures

Figure 1

Figure 1

Distribution of Minor-Allele Frequency by Collection Colors and line types for the densities of each collection are shown within the figure.

Figure 2

Figure 2

Genetic Structure Illustrated through Scatter Plots of Consecutive Principal Components Subject scores are colored by continental and/or ethnic origin (see legend). East Asian populations are indicated by varying point types. Percent of variation explained by each component is given in parentheses on each axis label.

Figure 3

Figure 3

Distribution of Subject-Level Principal Component 5 Scores by Reported Ancestry Each box and whisker indicates the median (heavy line), interquartile range (IQR, box), and minimum and maximum observations (whiskers). Whiskers are truncated at the last observation within 1.5 times the IQR from the edge of the box, with outliers shown individually. Plots for the remaining principal components are available in Figure S2, available online.

Figure 4

Figure 4

P-Plot Comparing Observed versus Expected Proportion of Associations over a Range of Significance Thresholds Separate lines are presented for each of the four control matching strategies. Results of the allelic exact test are shown on the left and genotypic exact tests on the right. A light gray line corresponds to unity.

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