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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.
| Version: | 1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp (≥ 1.0.0) |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2019-08-09 |
| DOI: | 10.32614/CRAN.package.PPMR |
| Author: | Zhongshang Yuan [aut], Xiang Zhou [aut], Michael Kleinsasser [cre] |
| Maintainer: | Michael Kleinsasser <mkleinsa at umich.edu> |
| BugReports: | https://github.com/umich-biostatistics/PPMR/issues |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | PPMR results |
| Reference manual: | PPMR.pdf |
| Package source: | PPMR_1.0.tar.gz |
| Windows binaries: | r-devel: PPMR_1.0.zip, r-release: PPMR_1.0.zip, r-oldrel: PPMR_1.0.zip |
| macOS binaries: | r-release (arm64): PPMR_1.0.tgz, r-oldrel (arm64): PPMR_1.0.tgz, r-release (x86_64): PPMR_1.0.tgz, r-oldrel (x86_64): PPMR_1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.