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Multi-Criteria Decision Making Approaches for Quality Control of Genome-Wide Association Studies

机译:全基因组关联研究质量控制的多标准决策方法

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摘要

Experimental errors in the genotyping phases of a Genome-Wide Association Study (GWAS) can lead to false positive findings and to spurious associations. An appropriate quality control phase could minimize the effects of this kind of errors. Several filtering criteria can be used to perform quality control. Currently, no formal methods have been proposed for taking into account at the same time these criteria and the experimenter’s preferences. In this paper we propose two strategies for setting appropriate genotyping rate thresholds for GWAS quality control. These two approaches are based on the Multi-Criteria Decision Making theory. We have applied our method on a real dataset composed by 734 individuals affected by Arterial Hypertension (AH) and 486 nonagenarians without history of AH. The proposed strategies appear to deal with GWAS quality control in a sound way, as they lead to rationalize and make explicit the experimenter’s choices thus providing more reproducible results.
机译:全基因组关联研究(GWAS)在基因分型阶段的实验错误可能导致假阳性结果和虚假关联。适当的质量控制阶段可以最大程度地减少此类错误的影响。几个过滤标准可用于执行质量控制。目前,尚未提出正式方法来同时考虑这些标准和实验者的偏好。在本文中,我们提出了两种为GWAS质量控制设置适当的基因分型率阈值的策略。这两种方法均基于“多标准决策”理论。我们已将我们的方法应用于由734名受动脉高血压(AH)影响的个体和486位无AH历史的非老年人组成的真实数据集。拟议的策略似乎可以合理地处理GWAS质量控制,因为它们可以合理化并明确表明实验者的选择,从而提供可重复的结果。

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