Genotype imputation for genome-wide association studies

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Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nature Genet. 39, 906–913 (2007).

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Howie, B. N., Donnelly, P. & Marchini, J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, e1000529 (2009). This paper describes the IMPUTE v2 method and carries out a comprehensive evaluation of several methods. This reference should be read as the follow-on from Reference 2, which describes IMPUTE v1.

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Servin, B. & Stephens, M. Imputation-based analysis of association studies: candidate regions and quantitative traits. PLoS Genet. 3, e114 (2007). The paper that describes the BIMBAM method for Bayesian multi-SNP and single SNP analysis using imputed data. Should be read together with Reference 8, which describes fastPHASE.

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Browning, B. & Browning, S. A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am. J. Hum. Genet. 84, 210–223 (2009).

Browning, S. Missing data imputation and haplotype phase inference for genome-wide association studies. Hum. Genet. 124 439–450 (2008). References 12–15 are a series of papers that describe the model underlying the BEAGLE method.

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Spencer, C. C. A., Su, Z., Donnelly, P. & Marchini, J. Designing genome-wide association studies: sample size, power, imputation, and the choice of genotyping chip. PLoS Genet. 5, e1000477 (2009).

Pei, Y., Li, J., Zhang, L., Papasian, C. & Deng, H. Analyses and comparison of accuracy of different genotype imputation methods. PLoS ONE 3, e3551 (2008).

Hao, K., Chudin, E., McElwee, J. & Schadt, E. E. Accuracy of genome-wide imputation of untyped markers and impacts on statistical power for association studies. BMC Genet. 10, 27 (2009).

Huang, L., Li, Y., Singleton, A., Hardy, J., Abecasis, G. et al. Genotype-imputation accuracy across worldwide human populations. Am. J. Hum. Genet. 84, 235–250 (2009). A useful reference that illustrates the performance of imputation in a range worldwide human populations when using the HapMap 2 reference panels.

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Zeggini, E. et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316, 1336–1341 (2007). One of the earliest examples of the use of imputation in meta-analysis. This paper combined three GWA studies and was able to identify several novel associations.

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Stephens, M. & Balding, D. Bayesian statistical methods for genetic association studies. Nature Rev. Genet. 10, 681–690 (2009). An excellent Review on the subject of using Bayesian statistical methods in association studies with a particular focus on the calculation, choice of priors and the interpretation of single SNP Bayes factors.

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