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Next-generation genotype imputation service and methods

2016; Nature Portfolio; Volume: 48; Issue: 10 Linguagem: Inglês

10.1038/ng.3656

1546-1718

Sayantan Das, Lukas Forer, Sebastian Schönherr, Carlo Sidore, Adam E. Locke, Alan Kwong, Scott Vrieze, Emily Y. Chew, Shawn Levy, Matt McGue, David Schlessinger, Dwight Stambolian, Po‐Ru Loh, William G. Iacono, Anand Swaroop, Laura J. Scott, Francesco Cucca, Florian Kronenberg, Michael Boehnke, Gonçalo R. Abecasis, Christian Fuchsberger,

Genetic Mapping and Diversity in Plants and Animals

Christian Fuchsberger, Gonçalo Abecasis and colleagues describe a new web-based imputation service that enables rapid imputation of large numbers of samples and allows convenient access to large reference panels of sequenced individuals. Their state space reduction provides a computationally efficient solution for genotype imputation with no loss in imputation accuracy. Genotype imputation is a key component of genetic association studies, where it increases power, facilitates meta-analysis, and aids interpretation of signals. Genotype imputation is computationally demanding and, with current tools, typically requires access to a high-performance computing cluster and to a reference panel of sequenced genomes. Here we describe improvements to imputation machinery that reduce computational requirements by more than an order of magnitude with no loss of accuracy in comparison to standard imputation tools. We also describe a new web-based service for imputation that facilitates access to new reference panels and greatly improves user experience and productivity.