A design study to identify inconsistencies in kinship information: The case of the 1000 Genomes project

Michaël Aupetit, Ehsan Ullah, Reda Rawi, H. Bensmail
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引用次数: 2

Abstract

Genome Wide Association Studies (GWAS) examine genetic variants in different individuals to detect variants associated to specific diseases. The 1000 Genomes project is such a collaborative research effort to sequence the genomes of at least 1000 participants of 26 different ethnicities, to establish a detailed summary of human genetic variation. The kinship information is a measure of individuals ancestor relationships within the considered populations. We study the design of kinship data visualizations allowing the experts to discover anomalies in GWAS data. The visual analysis of the 1000 Genomes Project kinship data reveals inconsistencies which call for a deeper analysis of the data quality within this project.
识别亲属信息不一致性的设计研究:以千人基因组计划为例
全基因组关联研究(GWAS)检查不同个体的遗传变异,以检测与特定疾病相关的变异。千人基因组计划就是这样一项合作研究,旨在对26个不同种族的至少1000名参与者的基因组进行测序,以建立人类遗传变异的详细摘要。亲属关系信息是在所考虑的群体中个体祖先关系的衡量标准。我们研究了亲属数据可视化的设计,允许专家发现GWAS数据中的异常。1000基因组计划亲缘关系数据的可视化分析揭示了不一致性,这需要对该项目中的数据质量进行更深入的分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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