Document Type

Conference Proceeding

Publication Date

6-17-2014

Department

Mathematics, Statistics, and Computer Science

Keywords

single-nucleotide variants, genetic analysis, single-marker approaches, multiple-marker approaches, genotype-phenotype

Abstract

Genotype errors are well known to increase type I errors and/or decrease power in related tests of genotypephenotype association, depending on whether the genotype error mechanism is associated with the phenotype. These relationships hold for both single and multimarker tests of genotype-phenotype association. To assess the potential for genotype errors in Genetic Analysis Workshop 18 (GAW18) data, where no gold standard genotype calls are available, we explored concordance rates between sequencing, imputation, and microarray genotype calls. Our analysis shows that missing data rates for sequenced individuals are high and that there is a modest amount of called genotype discordance between the 2 platforms, with discordance most common for lower minor allele frequency (MAF) single-nucleotide polymorphisms (SNPs). Some evidence for discordance rates that were different between phenotypes was observed, and we identified a number of cases where different technologies identified different bases at the variant site. Type I errors and power loss is possible as a result of missing genotypes and errors in called genotypes in downstream analysis of GAW18 data.

Comments

From Genetic Analysis Workshop 18, Stevenson, WA, USA. 13-17 October 2012.

Source Publication Title

BMC Proceedings

Volume

8

Issue

Supplement 1

First Page

S22

DOI

10.1186/1753-6561-8-S1-S22

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