Practical aspects of imputation-driven meta-analysis of genome-wide association studies
Practical aspects of imputation-driven meta-analysis of genome-wide association studies
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DOI：
10.1093/hmg/ddn288
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发表时间：
2008-10-15
影响因子：
3.5
通讯作者：
Voight, Benjamin F.
中科院分区：
文献类型：
--
作者：
de Bakker, Paul I. W.;Ferreira, Manuel A. R.;Voight, Benjamin F.
在全基因组关联研究取得巨大成功的激励下，大批研究人员正在积极努力交换和联合收割机遗传数据，以方便地发现人类共同特征的遗传风险因素。推动这些新努力的主要工具是插补，允许在各种基因型平台上收集数据的研究人员以统一的可交换格式共享数据，以及荟萃分析，以汇集基因型-表型关联的统计支持。由于许多团体正在形成合作，参与这些努力，本次审查收集了一系列的指导方针，实际细节和经验教训，从各种个人谁有助于这个问题。
Motivated by the overwhelming success of genome-wide association studies, droves of researchers are working vigorously to exchange and to combine genetic data to expediently discover genetic risk factors for common human traits. The primary tools that fuel these new efforts are imputation, allowing researchers who have collected data on a diversity of genotype platforms to share data in a uniformly exchangeable format, and meta-analysis for pooling statistical support for a genotype-phenotype association. As many groups are forming collaborations to engage in these efforts, this review collects a series of guidelines, practical detail and learned experiences from a variety of individuals who have contributed to the subject.