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Activity Number:
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417
- Contributed Poster Presentations: Section on Statistics in Epidemiology
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Type:
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Contributed
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Date/Time:
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Tuesday, August 1, 2017 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract #324159
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Title:
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Simulation of Realistic Genome-Wide Autosomal Genotype Data
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Author(s):
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David Umbach* and Min Shi and Alison Wise and Clare Weinberg
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Companies:
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National Institute of Environmental Health Sciences and National Institute of Environmental Health Sciences and unaffiliated and National Institute of Environmental Health Sciences
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Keywords:
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genetic simulation ;
case-parents design ;
case-control design ;
quantitative trait ;
GWAS
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Abstract:
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Evaluation of new statistical methods requires simulations. Generating realistic genotype simulations at a genome-wide scale remains challenging. Our goal is to simulate genome-wide single-nucleotide polymorphism (SNP) data that has realistic linkage disequilibrium (LD) and is amenable to spiking in multi-SNP causal effects. We start with data from an existing genome-wide association study (GWAS) of case-parent triads and add a hypothetical complement triad for each case triad; the complement triad has the same parental genotypes but the offspring carries the parental alleles not transmitted to the case. We construct each simulated triad genotype by resampling triples of chromosomal fragments in sequence from the mix of case and complement triads and concatenating them. This construction destroys any risk signals from the original data. Offspring can be assigned qualitative or quantitative traits probabilistically through a specified risk model. Our method can simulate genetically homogeneous or structured populations and can be adapted to simulate case-control data. Allele frequencies and LD structure in the original GWAS sample are largely preserved in the simulated data.
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Authors who are presenting talks have a * after their name.
