Package: PPMR 1.0.1

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_1.0.1.tar.gz
PPMR_1.0.1.tar.gz(r-4.7-arm64)PPMR_1.0.1.tar.gz(r-4.7-x86_64)PPMR_1.0.1.tar.gz(r-4.6-arm64)PPMR_1.0.1.tar.gz(r-4.6-x86_64)
PPMR_1.0.1.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://cran.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

2.00 score 1 stars 20 scripts 192 downloads 1 mentions 2 exports 2 dependencies

Last updated from:2172007b47. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK133
linux-devel-x86_64OK118
source / vignettesOK175
linux-release-arm64OK113
linux-release-x86_64OK127
wasm-releaseOK109

Exports:PMR_individualPMR_summary

Dependencies:RcppRcppArmadillo