协议(科学)
控制(管理)
荟萃分析
质量(理念)
全基因组关联研究
数据科学
计算机科学
生物
医学
遗传学
人工智能
替代医学
认识论
病理
内科学
哲学
基因型
单核苷酸多态性
基因
作者
Thomas W. Winkler,Felix R. Day,Damien C. Croteau‐Chonka,Andrew R. Wood,Adam E. Locke,Reedik Mägi,Teresa Ferreira,Tove Fall,Mariaelisa Graff,Anne E. Justice,Jian’an Luan,Stefan Gustafsson,Joshua C. Randall,Sailaja Vedantam,Tsegaselassie Workalemahu,Tuomas O. Kilpeläinen,André Scherag,Tõnu Esko,Zoltán Kutalik,Iris M. Heid,Ruth J. F. Loos
出处
期刊:Nature Protocols
[Springer Nature]
日期:2014-04-24
卷期号:9 (5): 1192-1212
被引量:464
标识
DOI:10.1038/nprot.2014.071
摘要
A protocol providing guidelines on the organizational aspects of genome-wide association meta-analyses and to implement quality control at the study file level, the meta-level across studies, and the meta-analysis output level. Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC at the study file level, the meta-level across studies and the meta-analysis output level. Real-world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for the use of a powerful and flexible software package called EasyQC. Precise timings will be greatly influenced by consortium size. For consortia of comparable size to the GIANT Consortium, this protocol takes a minimum of about 10 months to complete.
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