Package: PPMR 1.0

Michael Kleinsasser

PPMR: Probabilistic Two Sample Mendelian Randomization

Efficient statistical inference of two-sample MR (Mendelian Randomization) analysis. It can account for the correlated instruments and the horizontal pleiotropy, and can provide the accurate estimates of both causal effect and horizontal pleiotropy effect as well as the two corresponding p-values. There are two main functions in the 'PPMR' package. One is PMR_individual() for individual level data, the other is PMR_summary() for summary data.

Authors:Zhongshang Yuan [aut], Xiang Zhou [aut], Michael Kleinsasser [cre]

PPMR_1.0.tar.gz
PPMR_1.0.zip(r-4.7)PPMR_1.0.zip(r-4.6)PPMR_1.0.zip(r-4.5)
PPMR_1.0.tgz(r-4.6-x86_64)PPMR_1.0.tgz(r-4.6-arm64)PPMR_1.0.tgz(r-4.5-x86_64)PPMR_1.0.tgz(r-4.5-arm64)
PPMR_1.0.tar.gz(r-4.7-arm64)PPMR_1.0.tar.gz(r-4.7-x86_64)PPMR_1.0.tar.gz(r-4.6-arm64)PPMR_1.0.tar.gz(r-4.6-x86_64)
PPMR_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
PPMR/json (API)

# Install 'PPMR' in R:
install.packages('PPMR', repos = c('https://mrcieu.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/umich-biostatistics/ppmr/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

openblascppopenmp

3.30 score 2 stars 20 scripts 186 downloads 1 mentions 2 exports 2 dependencies

Last updated from:27e6c11167. Checks:8 NOTE, 2 OK, 3 FAIL. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE121
linux-devel-x86_64NOTE120
source / vignettesOK172
linux-release-arm64NOTE119
linux-release-x86_64NOTE115
macos-release-arm64NOTE76
macos-release-x86_64NOTE163
macos-oldrel-arm64FAIL57
macos-oldrel-x86_64FAIL151
windows-develNOTE131
windows-releaseNOTE100
windows-oldrelFAIL61
wasm-releaseOK137

Exports:PMR_individualPMR_summary

Dependencies:RcppRcppArmadillo