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://umich-biostatistics.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 199 downloads 1 mentions 2 exports 2 dependencies

Last updated from:27e6c11167. Checks:8 NOTE, 2 OK, 3 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE124
linux-devel-x86_64NOTE122
source / vignettesOK165
linux-release-arm64NOTE125
linux-release-x86_64NOTE119
macos-release-arm64NOTE92
macos-release-x86_64NOTE204
macos-oldrel-arm64FAIL64
macos-oldrel-x86_64FAIL191
windows-develNOTE128
windows-releaseNOTE137
windows-oldrelFAIL63
wasm-releaseOK109

Exports:PMR_individualPMR_summary

Dependencies:RcppRcppArmadillo