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/>.
|Author||Lerato E Magosi [aut], Jemma C Hopewell [aut], Martin Farrall [aut], Lerato E Magosi [cre]|
|Maintainer||Lerato E Magosi <email@example.com>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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