reproduction and in-depth evaluation of genome-wide association studies and genome-wide meta-analyses using summary statistics
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2017
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Abstract
In line with open-source genetics, we report a novel linear regression technique for genome-wide association studies (GWAS), called Open GWAS algoriTHm (OATH). When individual-level data are not available, OATH can not only completely reproduce reported results from an experimental model, but also recover underreported results from other alternative models with a different combination of nuisance parameters using naïve summary statistics (NSS). OATH can also reliably evaluate all reported results in-depth (e.g., p-value variance analysis), as demonstrated for 42 Arabidopsis phenotypes under three magnesium (Mg) conditions. In addition, OATH can be used for consortium-driven genome-wide association meta-analyses (GWAMA), and can greatly improve the flexibility of GWAMA. A prototype of OATH is available in the Genetic Analysis Repository (https://github.com/gc5k/GEAR).
| Reference Key |
niu2017g3:reproduction
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| Authors | ;Yao-Fang Niu;Chengyin Ye;Ji He;Fang Han;Long-Biao Guo;Hou-Feng Zheng;Guo-Bo Chen |
| Journal | separation and purification technology |
| Year | 2017 |
| DOI |
10.1534/g3.116.038877
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