getspres: SPRE Statistics for Exploring Heterogeneity in Meta-Analysis

An implementation of SPRE (standardised predicted random-effects) statistics in R to explore heterogeneity in genetic association meta- analyses, as described by Magosi et al. (2019) <doi:10.1093/bioinformatics/btz590>. SPRE statistics are precision weighted residuals that indicate the direction and extent with which individual study-effects in a meta-analysis deviate from the average genetic effect. Overly influential positive outliers have the potential to inflate average genetic effects in a meta-analysis whilst negative outliers might lower or change the direction of effect. See the 'getspres' website for documentation and examples <>.

Version: 0.2.0
Depends: R (≥ 3.1.0)
Imports: metafor (≥ 1.9-6), dplyr (≥ 0.4.1), plotrix (≥ 3.5-12), colorspace (≥ 1.2-6), RColorBrewer (≥ 1.1-2), colorRamps (≥ 2.3)
Suggests: knitr (≥ 1.10.5), testthat, covr, rmarkdown
Published: 2021-05-09
Author: Lerato E Magosi [aut], Jemma C Hopewell [aut], Martin Farrall [aut], Lerato E Magosi [cre]
Maintainer: Lerato E Magosi <magosil86 at>
License: MIT + file LICENSE
NeedsCompilation: no
Citation: getspres citation info
Materials: NEWS
In views: MetaAnalysis
CRAN checks: getspres results


Reference manual: getspres.pdf
Vignettes: getspres: A simple tool to identify overly influential outlier studies in genetic association meta-analyses.
Package source: getspres_0.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): getspres_0.2.0.tgz, r-release (x86_64): getspres_0.2.0.tgz, r-oldrel: getspres_0.2.0.tgz
Old sources: getspres archive


Please use the canonical form to link to this page.