Frontiers in Genetics (Jun 2011)

Cost-effective prediction of gender-labeling errors and estimation of gender-labeling error rates in candidate-gene association studies

  • Conghui eQu,
  • Johanna M. Schuetz,
  • Jeong Eun eMin,
  • Stephen eLeach,
  • Denise eDaley,
  • John J. Spinelli,
  • John J. Spinelli,
  • Angela eBrooks-Wilson,
  • Angela eBrooks-Wilson,
  • Jinko eGraham

DOI
https://doi.org/10.3389/fgene.2011.00031
Journal volume & issue
Vol. 2

Abstract

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We describe a statistical approach to predict gender-labeling errors in candidate-gene association studies, when Y-chromosome markers have not been included in the genotyping set. The approach adds value to methods that consider only the heterozygosity of X-chromosome SNPs, by incorporating available information about the intensity of X-chromosome SNPs in candidate genes relative to autosomal SNPs from the same individual. To our knowledge, no published methods formalize a framework in which heterozygosity and intensity are simultaneously taken into account. Our method offers the advantage that, in the genotyping set, no additional space is required beyond that already assigned to X-chromosome SNPs in the candidate genes. We also show how the predictions can be used in a two-phase sampling design to estimate the gender-labeling error rates for an entire study, at a fraction of the cost of a conventional design.

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