Next-generation genotype imputation service and methods

By Sayantani Das, Lukas Forer, S. Schönherr, C. Sidore, A. Locke, Alan M. Kwong, Scott Vrieze, Emily Y. Chew, S. Levy, Matthew McGue and 11 more. Nature Genetics, 2016

3,622 citations recorded by the source corpus.

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.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/17d093b762ccc8348a579c412a14e3c0a66a8931

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Citations in the corpus

The power of genetic diversity in genome-wide association studies of lipids (2021, methodology): “…each cohort perform imputation to 1000 Genomes Phase 3 v5 (1KGP3), with European ancestry cohorts additionally imputing with the Haplotype Reference Consortium (HRC) panel using the Michigan Imputation Server (https:// imputationserver.sph.umich.edu/index.html#!), which uses Minimac software 43 .”
Polygenic prediction of weight and obesity trajectories from birth to adulthood (2019, neutral): “REAGENT or RESOURCE SOURCE IDENTIFIER Software and Algorithms GIANT body-mass index association statistics Locke et al., 2015 https://portals.broadinstitute.org/collaboration/giant/ index.php/Main_Page 1000 Genomes Phase 3 1000 Genomes Project Consortium et al., 2015 http://www.internationalgenome.o”
Reduced signal for polygenic adaptation of height in UK Biobank (2018, methodology): “Polygenic score analyses Population genetic datasets 1000 Genomes Phase 3 VCF files were downloaded from the 1000 Genomes website, and VCF files for the Human Origins dataset were downloaded from the ‘Affymetrix Human Origins fully public dataset’ link on the Reich lab website and subsequently imput”
Large-scale whole-genome sequencing of three diverse Asian populations in Singapore (2018, neutral): “Given a reference panel, we pre-phased each populations from HGDP and SGVP using reference-based phasing algorithm in EAGLE2,(33) followed by imputation using Minimac4.(7) Imputation error rate was computed for each population as the genotype discordance rate of the 4,633 masked SNPs.”
Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program (2019, methodology): “We removed all singleton sites and compressed the haplotype chunks into m3vcf format 109 .”
Multi-Ethnic Genome-wide Association Study for Atrial Fibrillation (2018, methodology): “1.(40) Studies without available HRC imputation were included based on imputation to the 1000 Genomes Phase 1 integrated v3 panel (March 2012).”
Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics (2016, methodology): “1 2016 panel [44] (via minimac3) were carried out by the Michigan Imputation Server [45].”