SPRE Statistics for Exploring Heterogeneity in Meta-Analysis R package getspres version 0.2.0 CRAN Task View: MetaAnalysis (https://CRAN.R-project.org/view=MetaAnalysis) 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 <https://magosil86.github.io/getspres/>. Software 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 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=getspres/LICENSE) 2021-05-09 application/tgz https://CRAN.R-project.org/package=getspres doi:10.32614/CRAN.package.getspres