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
<https://magosil86.github.io/getspres/>.
| 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 gmail.com> |
| BugReports: |
https://github.com/magosil86/getspres/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://magosil86.github.io/getspres/ |
| NeedsCompilation: |
no |
| Citation: |
getspres citation info |
| Materials: |
NEWS |
| In views: |
MetaAnalysis |
| CRAN checks: |
getspres results |
Documentation:
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