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Evaluating variations of genotype calling: a potential source of spurious associations in genome-wide association studies

机译:评估基因型调用的变异:基因组关联研究中的潜在杂散源

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摘要

Genome-wide association studies (GWAS) examine the entire human genome with the goal of identifying genetic variants (usually single nucleotide polymorphisms (SNPs)) that are associated with phenotypic traits such as disease status and drug response. The discordance of significantly associated SNPs for the same disease identified from different GWAS indicates that false associations exist in such results. In addition to the possible sources of spurious associations that have been investigated and discussed intensively, such as sample size and population stratification, an accurate and reproducible genotype calling algorithm is required for concordant GWAS results from different studies. However, variations of genotype calling of an algorithm and their effects on significantly associated SNPs identified in downstream association analyses have not been systematically investigated. In this paper, the variations of genotype calling using the Bayesian Robust Linear Model with Mahalanobis distance classifier (BRLMM) algorithm and the resulting influence on the lists of significantly associated SNPs were evaluated using the raw data of 270 HapMap samples analysed with the Affymetrix Human Mapping 500K Array Set (Affy500K) by changing algorithmic parameters. Modified were the Dynamic Model (DM) call confidence threshold (threshold) and the number of randomly selected SNPs (size). Comparative analysis of the calling results and the corresponding lists of significantly associated SNPs identified through association analysis revealed that algorithmic parameters used in BRLMM affected the genotype calls and the significantly associated SNPs. Both the threshold and the size affected the called genotypes and the lists of significantly associated SNPs in association analysis. The effect of the threshold was much larger than the effect of the size. Moreover, the heterozygous calls had lower consistency compared to the homozygous calls.
机译:基因组 - 宽协会研究(GWAs)以鉴定与表型特性等疾病状态和药物反应相关的遗传变体(通常是单核苷酸多态性(SNP))的目标检查整个人类基因组。对于从不同GWA鉴定的相同疾病的显着相关的SNP具有明显相关的SNP表明在这种结果中存在错误关联。除了已经研究和讨论的杂种关联的可能源来源之外,例如样本大小和人口分层,伴有不同研究的协调GWA是一种准确和可重复的基因型呼叫算法。然而,尚未系统地研究了算法对算法的基因型调用及其对显着相关的SNP的效果的变化,并未得到系统地研究了下游关联分析中鉴定的显着相关的SNP。在本文中,使用使用Affymetrix人类映射分析的270 HapMap样本的原始数据来评估使用Mahalanobis距离分类器(BRLMM)算法(BRLMM)算法(BRLMM)算法(BRLMM)算法(BRLMM)算法的基因型呼叫的变化以及对显着相关的SNP的列表进行评估通过更改算法参数500k阵列组(AFFY500K)。修改是动态模型(DM)呼叫置信阈值(阈值)和随机选择的SNP(大小)的数量。呼叫结果的比较分析和通过关联分析确定的显着相关的SNP的相应列表显示,BRLMM中使用的算法参数影响了基因型呼叫和显着相关的SNP。阈值和大小都影响了所谓的基因型和关联分析中显着相关的SNP的列表。阈值的效果远大于尺寸的效果。此外,与纯合子呼叫相比,杂合子呼叫较低。

著录项

  • 来源
    《Journal of genetics》 |2011年第1期|共10页
  • 作者单位

    Division of Systems Toxicology National Center for Toxicological Research US Food and Drug Administration 3900 NCTR Road Jefferson AR 72079 USA;

    Division of Systems Toxicology National Center for Toxicological Research US Food and Drug Administration 3900 NCTR Road Jefferson AR 72079 USA;

    Division of Systems Toxicology National Center for Toxicological Research US Food and Drug Administration 3900 NCTR Road Jefferson AR 72079 USA;

    Division of Systems Toxicology National Center for Toxicological Research US Food and Drug Administration 3900 NCTR Road Jefferson AR 72079 USA;

    Division of Systems Toxicology National Center for Toxicological Research US Food and Drug Administration 3900 NCTR Road Jefferson AR 72079 USA;

    Z-Tech Corp ICF International Company at National Center for Toxicological Research US Food and Drug Administration 3900 NCTR Road Jefferson AR 72079 USA;

    Division of Systems Toxicology National Center for Toxicological Research US Food and Drug Administration 3900 NCTR Road Jefferson AR 72079 USA;

    Division of Systems Toxicology National Center for Toxicological Research US Food and Drug Administration 3900 NCTR Road Jefferson AR 72079 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 遗传学;
  • 关键词

    genotype calling; genome-wide association studies; missing call rate; calling algorithm; spurious association;

    机译:基因型呼叫;基因组关联研究;缺失呼叫率;呼叫算法;虚假协会;

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