If results from a meta-GWAS are used for validation in one of the cohorts that was included in the meta-analysis, this will yield biased (i.e. too optimistic) results. The validation cohort needs to be independent from the meta-Genome-Wide-Association-Study (meta-GWAS) results. 'MetaSubtract' will subtract the results of the respective cohort from the meta-GWAS results analytically without having to redo the meta-GWAS analysis using the leave-one-out methodology. It can handle different meta-analyses methods and takes into account if single or double genomic control correction was applied to the original meta-analysis. It can also handle different meta-analysis methods. It can be used for whole GWAS, but also for a limited set of genetic markers. See for application: Nolte I.M. et al. (2017); <doi:10.1038/ejhg.2017.50>.
| Version: | 1.60 |
| Published: | 2020-03-30 |
| Author: | Ilja M. Nolte |
| Maintainer: | Ilja M. Nolte <i.m.nolte at umcg.nl> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| In views: | MetaAnalysis |
| CRAN checks: | MetaSubtract results |
| Reference manual: | MetaSubtract.pdf |
| Package source: | MetaSubtract_1.60.tar.gz |
| Windows binaries: | r-devel: MetaSubtract_1.60.zip, r-release: MetaSubtract_1.60.zip, r-oldrel: MetaSubtract_1.60.zip |
| macOS binaries: | r-release: MetaSubtract_1.60.tgz, r-oldrel: MetaSubtract_1.60.tgz |
| Old sources: | MetaSubtract archive |
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