We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Reproduction and In-Depth Evaluation of Genome-Wide Association Studies and Genome-Wide Meta-analyses Using Summary Statistics.
- Authors
Yao-Fang Niu; Chengyin Ye; Ji He; Fang Han; Long-Biao Guo; Hou-Feng Zheng; Guo-Bo Chen
- Abstract
In line with open-source genetics, we report a novel linear regression technique for genomewide 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.
- Subjects
GENE mapping; ARABIDOPSIS; SINGLE nucleotide polymorphisms
- Publication
G3: Genes | Genomes | Genetics, 2017, Vol 7, Issue 3, p943
- ISSN
2160-1836
- Publication type
Article
- DOI
10.1534/g3.116.038877