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Volumn 14, Issue 4, 2013, Pages 300-

Response to sul and Eskin

Author keywords

[No Author keywords available]

Indexed keywords

GENE FREQUENCY; LETTER; POPULATION DIFFERENTIATION; POPULATION STRUCTURE; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL;

EID: 84875216069     PISSN: 14710056     EISSN: 14710064     Source Type: Journal    
DOI: 10.1038/nrg2813-c2     Document Type: Letter
Times cited : (4)

References (13)
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  • 2
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    • New approaches to population stratification in genome-wide association studies
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  • 3
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    • Variance component model to account for sample structure in genome-wide association studies
    • Kang, H. M. et al. Variance component model to account for sample structure in genome-wide association studies. Nature Genet. 42, 348-354 (2010).
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    • Kang, H.M.1
  • 4
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    • Mixed linear model approach adapted for genome-wide association studies
    • Zhang, Z. et al. Mixed linear model approach adapted for genome-wide association studies. Nature Genet. 42, 355-360 (2010).
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    • Zhang, Z.1
  • 5
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    • Model-based approach for analysis of spatial structure in genetic data
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  • 6
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    • An efficient multi-locus mixedmodel approach for genome-wide association studies in structured populations
    • Segura, V. et al. An efficient multi-locus mixedmodel approach for genome-wide association studies in structured populations. Nature Genet. 44, 825-830 (2012).
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    • Segura, V.1
  • 7
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    • Genome-wide efficient mixedmodel analysis for association studies
    • Zhou, X. & Stephens, M. Genome-wide efficient mixedmodel analysis for association studies. Nature Genet. 44, 821-824 (2012).
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    • Zhou, X.1    Stephens, M.2
  • 8
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    • The nature of confounding in genome-wide association studies
    • Vilhjalmsson, B. J. & Nordborg, M. The nature of confounding in genome-wide association studies. Nature Rev. Genet. 14, 1-2 (2013).
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  • 9
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    • Inferences from genomic models in stratified populations
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  • 10
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    • Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis
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