getmstatistic: Quantifying Systematic Heterogeneity in Meta-Analysis

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 <> for statistical statistical theory, documentation and examples.

Package details

AuthorLerato E Magosi [aut], Jemma C Hopewell [aut], Martin Farrall [aut], Lerato E Magosi [cre]
MaintainerLerato E Magosi <[email protected]>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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getmstatistic documentation built on June 9, 2017, 1:02 a.m.