title: Reproduction and In-Depth Evaluation of Genome-Wide Association Studies and Genome-Wide Meta-analyses Using Summary Statistics.
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 42Arabidopsisphenotypes 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).
authors.affiliation: State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006 Zhejiang, China.
authors.forename: Yao-Fang
authors.initials: YF
authors.lastname: Niu
authors.affiliation: Department of Health Management, College of Medicine, Hangzhou Normal University, Hangzhou, 310021 Zhejiang, China.
authors.forename: Chengyin
authors.initials: C
authors.lastname: Ye
authors.affiliation: Department of Neurology, Peking University Third Hospital, Beijing 100191, China.
authors.forename: Ji
authors.initials: J
authors.lastname: He
authors.affiliation: Department of Pulmonary and Critical Care Medicine, Peking University People's Hospital, Beijing 100044, China.
authors.forename: Fang
authors.initials: F
authors.lastname: Han
authors.affiliation: State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006 Zhejiang, China.
authors.forename: Long-Biao
authors.initials: LB
authors.lastname: Guo
authors.affiliation: Institute of Aging Research, College of Medicine, Hangzhou Normal University, Hangzhou, 310021 Zhejiang, China hfzheng@hznu.edu.cn chenguobo@gmail.com.|The Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015 Zhejiang, China.
authors.forename: Hou-Feng
authors.initials: HF
authors.lastname: Zheng
authors.affiliation: Evergreen Landscape and Architecture Studio, Hangzhou, 310026 Zhejiang, China hfzheng@hznu.edu.cn chenguobo@gmail.com.
authors.forename: Guo-Bo
authors.identifier: 0000-0001-5475-8237
authors.initials: GB
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D017360:Arabidopsis / Q000187:drug effects / Q000235:genetics; D044466:Asian People / Q000235:genetics; D015331:Cohort Studies; D003198:Computer Simulation; D056426:Genetic Loci; D055106:Genome-Wide Association Study; D006801:Humans; D008274:Magnesium / Q000494:pharmacology; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D019655:Quantitative Trait, Heritable; D015203:Reproducibility of Results; D012098:Reproduction / Q000235:genetics*; D013223:Statistics as Topic
chemical_list: D008274:Magnesium
keywords: Arabidopsis; GEAR; GWAMA; GWAS; magnesium; meta-analyses; naïve summary statistics; reproducibility; transparency