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Missing data imputation and haplotype phase inference for genome-wide association studies Browning SRHum Genet 2008[Dec]; 124 (5): 439-50Imputation of missing data and the use of haplotype-based association tests can improve the power of genome-wide association studies (GWAS). In this article, I review methods for haplotype inference and missing data imputation, and discuss their application to GWAS. I discuss common features of the best algorithms for haplotype phase inference and missing data imputation in large-scale data sets, as well as some important differences between classes of methods, and highlight the methods that provide the highest accuracy and fastest computational performance.|Algorithms[MESH]|Biometry[MESH]|Data Interpretation, Statistical[MESH]|Databases, Genetic[MESH]|Genetic Markers[MESH]|Genetic Variation[MESH]|Genetics, Medical/*statistics & numerical data[MESH]|Genome-Wide Association Study/*statistics & numerical data[MESH]|Genotype[MESH]|Haplotypes[MESH]|Humans[MESH]|Markov Chains[MESH]|Models, Genetic[MESH]|Models, Statistical[MESH]|Polymorphism, Single Nucleotide[MESH] |
