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.zip(r-4.7-x86_64)PPMR_1.0.1.zip(r-4.7-arm64)PPMR_1.0.1.zip(r-4.6-x86_64)PPMR_1.0.1.zip(r-4.6-arm64)
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✨
DESCRIPTION
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

1.98 score 1 stars 19 scripts 228 downloads 1 mentions 2 exports 2 dependencies

Last updated from:2172007b47. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK96
linux-devel-x86_64OK122
source / vignettesOK204
linux-release-arm64OK86
linux-release-x86_64OK109
windows-devel-arm64OK234
windows-devel-x86_64OK118
windows-release-arm64OK204
windows-release-x86_64OK113
wasm-releaseOK108

Exports:PMR_individualPMR_summary

Dependencies:RcppRcppArmadillo