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The effects of errors in the specification of genotype of a single nucleotide polymorphism (SNP) on the chi-squared test of association between disease and SNP type.

机译：单核苷酸多态性（SNP）基因型规范中的错误对疾病与SNP类型之间关联性的卡方检验的影响。

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摘要

The purpose of this paper is to study the effects of SNP genotyping errors on the 2 x 3 chi2 test of independence. First, we would like to ask what errors are most costly, in terms of increased sample size to maintain constant asymptotic power and significance level (SSN), when performing case-control studies of genetic association. The most costly error is recording the more common homozygote as the less common homozygote. In general, recording a more common genotype as a less common genotype is more costly than the reverse error with cost increasing as the difference between genotype frequencies increases.; Then we ask what classification rules minimize the SSN when the underlying datum of genotyping follows a three-component normal mixture distribution. That is, for genotype AA, the datum is N( dL,1); for genotype AB, N(0,1); and for genotype BB, N(dR,1), with dL 0 dR. The rule to classify an observation as the genotype with closer mean (called the halfway rule) has SSN within 6% of the optimal SSN.; In practice, a "no-call" procedure is sometimes used in which borderline observations are not classified. This procedure has the simultaneous effect of reducing the genotype error rate and the expected number of genotypes observed. Both quantities affect the expected power of the chi-squared statistic. The benefits of reduced genotype error rate are almost exactly balanced by the losses due to reduced genotype observations. For an underlying univariate normal mixture of genotype classification to be analyzed with a 2 x 3 chi-squared test, there is little, if any, increase in power using a no-call procedure.
机译：本文的目的是研究SNP基因分型错误对2 x 3 chi2独立性测试的影响。首先，我们想问一下在进行基因关联的病例对照研究时，为了保持恒定的渐近能力和显着性水平（SSN），增加样本量会导致哪些错误代价最高。最昂贵的错误是将更常见的纯合子记录为不常见的纯合子。通常，将较常见的基因型记录为较不常见的基因型要比反向误差更昂贵，并且随着基因型频率之间的差异增加，成本也会增加。然后，当基因分型的基础数据遵循三成分正态混合分布时，我们问什么分类规则将SSN最小化。也就是说，对于基因型AA，数据为N（dL，1）；对于基因型AB，N（0,1）;对于BB型，N（dR，1），dL <0

著录项

  • 作者

    Kang, Sun Jung.;

  • 作者单位

    State University of New York at Stony Brook.;

  • 授予单位 State University of New York at Stony Brook.;
  • 学科 Statistics.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 68 p.
  • 总页数 68
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 统计学;
  • 关键词

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