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.tgz(r-4.6-x86_64)PPMR_1.0.tgz(r-4.6-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✨
DESCRIPTION
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 286 downloads 1 mentions 2 exports 2 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE167
linux-devel-x86_64NOTE165
source / vignettesOK166
linux-release-arm64NOTE160
linux-release-x86_64NOTE125
macos-release-arm64NOTE95
macos-release-x86_64NOTE193
macos-oldrel-arm64FAIL62
macos-oldrel-x86_64FAIL173
windows-develNOTE108
windows-releaseNOTE109
windows-oldrelFAIL83
wasm-releaseOK133

Exports:PMR_individualPMR_summary

Dependencies:RcppRcppArmadillo