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29
Pca-correlated snps for structure identification in worldwide human populations
- PLOS Genetics
, 2007
"... Existing methods to ascertain small sets of markers for the identification of human population structure require prior knowledge of individual ancestry. Based on Principal Components Analysis (PCA), and recent results in theoretical computer science, we present a novel algorithm that, applied on gen ..."
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Cited by 23 (10 self)
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Existing methods to ascertain small sets of markers for the identification of human population structure require prior knowledge of individual ancestry. Based on Principal Components Analysis (PCA), and recent results in theoretical computer science, we present a novel algorithm that, applied on genomewide data, selects small subsets of SNPs (PCAcorrelated SNPs) to reproduce the structure found by PCA on the complete dataset, without use of ancestry information. Evaluating our method on a previously described dataset (10,805 SNPs, 11 populations), we demonstrate that a very small set of PCA-correlated SNPs can be effectively employed to assign individuals to particular continents or populations, using a simple clustering algorithm. We validate our methods on the HapMap populations and achieve perfect intercontinental differentiation with 14 PCA-correlated SNPs. The Chinese and Japanese populations can be easily differentiated using less than 100 PCA-correlated SNPs ascertained after evaluating 1.7 million SNPs from
Population structure and cryptic relatedness in genetic association studies
- Statistical Science
, 2009
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X (2008) Genome-wide association studies: implications for multiethnic samples
- Hum Mol Genet
"... The current gene mapping for complex diseases is heavily weighted by studies of population samples from northern Europe. To capture the full range of genetic diversity and exploit the potential of genetic epidemiol-ogy to identify important variants, multiple additional populations will need to be e ..."
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Cited by 18 (0 self)
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The current gene mapping for complex diseases is heavily weighted by studies of population samples from northern Europe. To capture the full range of genetic diversity and exploit the potential of genetic epidemiol-ogy to identify important variants, multiple additional populations will need to be examined. The conduct of genome-wide association studies will therefore confront many of the challenges identified in the first gener-ation of candidate gene and linkage studies, with a substantial increase in complexity. Initial efforts to map causal effects will have to take account of varying patterns of linkage disequilibrium through careful attention to local haplotype structure. Refined statistical techniques that permit joint analyses of samples from mul-tiple populations will also be required, as well as improved methods to account for on-going gene flow between populations with geographically distinct ancestral origins. This variation can either be an impedi-ment, slowing the process of replication, or an opportunity, allowing finer dissection of the relevant variants. Clinical translation of these data will present major challenges. Large cosmopolitan populations, such as those found in large urban centers, are likely to exhibit both known and cryptic sub-structure across groups, as well as admixture within individuals. Great care will need to be devoted to generalizability of association findings to avoid their premature adoption as predictive tests in the face of this widespread het-erogeneity.
Measuring and using admixture to study the genetics of complex diseases
- Hum. Genomics
, 2003
"... Admixture is an important evolutionary force that can and should be used in efforts to apply genomic data and technology to the study of complex disease genetics. Admixture linkage disequilibrium (ALD) is created by the process of admixture and, in recently admixed populations, extends for substanti ..."
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Cited by 9 (0 self)
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Admixture is an important evolutionary force that can and should be used in efforts to apply genomic data and technology to the study of complex disease genetics. Admixture linkage disequilibrium (ALD) is created by the process of admixture and, in recently admixed populations, extends for substantial distances (of the order of 10 to 20 cM). The amount of ALD generated depends on the level of admixture, ancestry information content of markers and the admixture dynamics of the population, and thus influences admixture mapping (AM). The authors discuss different models of admixture and how these can have an impact on the success of AM studies. Selection of markers is important, since markers informative for parental population ancestry are required and these are uncommon. Rarely does the process of admixture result in a population that is uniform for individual admixture levels, but instead there is substantial population stratification. This stratification can be understood as variation in individual admixtures and can be both a source of statistical power for ancestry–phenotype correlation studies as well as a confounder in causing false-positives in gene association studies. Methods to detect and control for stratification in case/control and AM studies are reviewed, along with recent studies showing individual ancestry–phenotype correlations. Using skin pigmentation as a model phenotype, implications of AM in complex disease gene mapping studies are discussed. Finally, the article discusses some limitations of this approach that should be considered when designing an effective AM study.
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"... Vol. 26 ISMB 2010, pages i208–i216 doi:10.1093/bioinformatics/btq191 Multi-population GWA mapping via multi-task regularized regression ..."
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Vol. 26 ISMB 2010, pages i208–i216 doi:10.1093/bioinformatics/btq191 Multi-population GWA mapping via multi-task regularized regression
ARTICLE ROADTRIPS: Case-Control Association Testing with Partially or Completely Unknown Population and Pedigree Structure
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"... Bioinformatic analysis of autism positional candidate genes using biological databases and computational gene network prediction ..."
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Bioinformatic analysis of autism positional candidate genes using biological databases and computational gene network prediction
The Use of Race Variables in Genetic Studies of Complex Traits and the Goal of Reducing Health Disparities
"... The use of racial variables in genetic studies has become a matter of intense public debate, with implications for re-search design and translation into practice. Using research on smoking as a springboard, the authors examine the history of racial categories, current research practices, and argumen ..."
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The use of racial variables in genetic studies has become a matter of intense public debate, with implications for re-search design and translation into practice. Using research on smoking as a springboard, the authors examine the history of racial categories, current research practices, and arguments for and against using race variables in genetic analyses. The authors argue that the sociopolitical constructs appropriate for monitoring health disparities are not appropriate for use in genetic studies investigating the etiology of complex diseases. More powerful methods for addressing population structure exist, and race vari-ables are unacceptable as gross proxies for numerous social/environmental factors that disproportionately affect minority populations. The authors conclude with recom-mendations for genetic researchers and policymakers,
