Quantifying Systematic Heterogeneity in Meta-Analysis R package getmstatistic version 0.2.2 CRAN Task View: MetaAnalysis (https://CRAN.R-project.org/view=MetaAnalysis) Quantifying systematic heterogeneity in meta-analysis using R. The M statistic aggregates heterogeneity information across multiple variants to, identify systematic heterogeneity patterns and their direction of effect in meta-analysis. It's primary use is to identify outlier studies, which either show "null" effects or consistently show stronger or weaker genetic effects than average across, the panel of variants examined in a GWAS meta-analysis. In contrast to conventional heterogeneity metrics (Q-statistic, I-squared and tau-squared) which measure random heterogeneity at individual variants, M measures systematic (non-random) heterogeneity across multiple independently associated variants. Systematic heterogeneity can arise in a meta-analysis due to differences in the study characteristics of participating studies. Some of the differences may include: ancestry, allele frequencies, phenotype definition, age-of-disease onset, family-history, gender, linkage disequilibrium and quality control thresholds. See <https://magosil86.github.io/getmstatistic/> for statistical statistical theory, documentation and examples. Software Depends: R (>= 3.1.0) Imports: ggplot2 (>= 1.0.1), gridExtra (>= 0.9.1), gtable (>= 0.1.2), metafor (>= 1.9-6), psych (>= 1.5.1), stargazer (>= 5.1) Suggests: foreign (>= 0.8-62), knitr (>= 1.10.5), testthat, covr, rmarkdown Lerato E Magosi <magosil86@gmail.com> Comprehensive R Archive Network (CRAN) Lerato E Magosi [aut], Jemma C Hopewell [aut], Martin Farrall [aut], Lerato E Magosi [cre] MIT + file LICENSE (https://CRAN.R-project.org/package=getmstatistic/LICENSE) 2021-05-09 application/tgz https://CRAN.R-project.org/package=getmstatistic doi:10.32614/CRAN.package.getmstatistic