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Imputation aware tag SNP selection to improve power for multi-ethnic association studies

View ORCID ProfileGenevieve L. Wojcik, View ORCID ProfileChristian Fuchsberger, Daniel Taliun, Ryan Welch, Alicia R Martin, Suyash Shringarpure, Christopher S. Carlson, Goncalo Abecasis, Hyun Min Kang, Michael Boehnke, Carlos D. Bustamante, Christopher R. Gignoux, Eimear E. Kenny
doi: https://doi.org/10.1101/105551
Genevieve L. Wojcik
1Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
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  • ORCID record for Genevieve L. Wojcik
Christian Fuchsberger
2Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
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Daniel Taliun
2Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
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Ryan Welch
2Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
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Alicia R Martin
1Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
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Suyash Shringarpure
1Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
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Christopher S. Carlson
3Fred Hutchinson Cancer Center, University of Washington, Seattle, WA, USA
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Goncalo Abecasis
2Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
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Hyun Min Kang
2Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
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Michael Boehnke
2Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
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Carlos D. Bustamante
1Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
4Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
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Christopher R. Gignoux
1Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
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Eimear E. Kenny
5Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
6The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
7The Icahn Institute of Multiscale Biology and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
8The Center for Statistical Genetics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Abstract

The emergence of very large cohorts in genomic research has facilitated a focus on genotype-imputation strategies to power rare variant association. Consequently, a new generation of genotyping arrays are being developed designed with tag single nucleotide polymorphisms (SNPs) to improve rare variant imputation. Selection of these tag SNPs poses several challenges as rare variants tend to be continentally-or even population-specific and reflect fine-scale linkage disequilibrium (LD) structure impacted by recent demographic events. To explore the landscape of tag-able variation and guide design considerations for large-cohort and biobank arrays, we developed a novel pipeline to select tag SNPs using the 26 population reference panel from Phase of the 1000 Genomes Project. We evaluate our approach using leave-one-out internal validation via standard imputation methods that allows the direct comparison of tag SNP performance by estimating the correlation of the imputed and real genotypes for each iteration of potential array sites. We show how this approach allows for an assessment of array design and performance that can take advantage of the development of deeper and more diverse sequenced reference panels. We quantify the impact of demography on tag SNP performance across populations and provide population-specific guidelines for tag SNP selection. We also examine array design strategies that target single populations versus multi-ethnic cohorts, and demonstrate a boost in performance for the latter can be obtained by prioritizing tag SNPs that contribute information across multiple populations simultaneously. Finally, we demonstrate the utility of improved array design to provide meaningful improvements in power, particularly in trans-ethnic studies. The unified framework presented will enable investigators to make informed decisions for the design of new arrays, and help empower the next phase of rare variant association for global health.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 03, 2017.
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Imputation aware tag SNP selection to improve power for multi-ethnic association studies
Genevieve L. Wojcik, Christian Fuchsberger, Daniel Taliun, Ryan Welch, Alicia R Martin, Suyash Shringarpure, Christopher S. Carlson, Goncalo Abecasis, Hyun Min Kang, Michael Boehnke, Carlos D. Bustamante, Christopher R. Gignoux, Eimear E. Kenny
bioRxiv 105551; doi: https://doi.org/10.1101/105551
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Imputation aware tag SNP selection to improve power for multi-ethnic association studies
Genevieve L. Wojcik, Christian Fuchsberger, Daniel Taliun, Ryan Welch, Alicia R Martin, Suyash Shringarpure, Christopher S. Carlson, Goncalo Abecasis, Hyun Min Kang, Michael Boehnke, Carlos D. Bustamante, Christopher R. Gignoux, Eimear E. Kenny
bioRxiv 105551; doi: https://doi.org/10.1101/105551

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