Assessing the Impact of Non-Differential Genotyping Errors on Rare Variant Tests of Association

Scott Powers*, Shyam Gopalakrishnan, Nathan Tintle

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

14 Citations (Scopus)

Abstract

Background/Aims: We aim to quantify the effect of non-differential genotyping errors on the power of rare variant tests and identify those situations when genotyping errors are most harmful. Methods: We simulated genotype and phenotype data for a range of sample sizes, minor allele frequencies, disease relative risks and numbers of rare variants. Genotype errors were then simulated using five different error models covering a wide range of error rates. Results: Even at very low error rates, misclassifying a common homozygote as a heterozygote translates into a substantial loss of power, a result that is exacerbated even further as the minor allele frequency decreases. While the power loss from heterozygote to common homozygote errors tends to be smaller for a given error rate, in practice heterozygote to homozygote errors are more frequent and, thus, will have measurable impact on power. Conclusion: Error rates from genotype-calling technology for next-generation sequencing data suggest that substantial power loss may be seen when applying current rare variant tests of association to called genotypes.

Original languageEnglish
JournalHuman Heredity
Volume72
Issue number3
Pages (from-to)153-160
Number of pages8
ISSN0001-5652
DOIs
Publication statusPublished - 2011
Externally publishedYes

Keywords

  • Case-control
  • Misclassification
  • Power
  • Sequencing data

Cite this