MetaSubtract: Subtracting Summary Statistics of One or more Cohorts from Meta-GWAS Results

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
DOI: 10.32614/CRAN.package.MetaSubtract
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

Documentation:

Reference manual: MetaSubtract.pdf

Downloads:

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 (arm64): MetaSubtract_1.60.tgz, r-oldrel (arm64): MetaSubtract_1.60.tgz, r-release (x86_64): MetaSubtract_1.60.tgz, r-oldrel (x86_64): MetaSubtract_1.60.tgz
Old sources: MetaSubtract archive

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