Next-generation genotype imputation service and methods

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 efficie...

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Bibliographic Details
Published in:Nature genetics Vol. 48; no. 10; pp. 1284 - 1287
Main Authors: Das, Sayantan, Forer, Lukas, Schönherr, Sebastian, Sidore, Carlo, Locke, Adam E, Kwong, Alan, Vrieze, Scott I, Chew, Emily Y, Levy, Shawn, McGue, Matt, Schlessinger, David, Stambolian, Dwight, Loh, Po-Ru, Iacono, William G, Swaroop, Anand, Scott, Laura J, Cucca, Francesco, Kronenberg, Florian, Boehnke, Michael, Abecasis, Gonçalo R, Fuchsberger, Christian
Format: Journal Article
Language:English
Published: New York Nature Publishing Group US 01.10.2016
Nature Publishing Group
Subjects:
45
45/23
45/43
631/114/2785
631/208/205/2138
631/208/514
Accuracy
Agriculture
Algorithms
Analysis
Animal Genetics and Genomics
Biomedicine
Cancer Research
Computer Simulation
Gene Function
Genetic aspects
Genome-Wide Association Study
Genomes
Genomics
Genotype
Genotype & phenotype
Haplotypes
Human Genetics
Humans
Internet
letter
Methods
Researchers
Software
Studies
ISSN:1061-4036, 1546-1718, 1546-1718
Online Access:Get full text
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Summary: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.
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These authors jointly directed this work.
ISSN:1061-4036
1546-1718
1546-1718
DOI:10.1038/ng.3656