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Provides functions to implement a hierarchical approach which is designed to perform joint analysis of summary statistics using the framework of Mendelian Randomization or transcriptome analysis. Reference: Lai Jiang, Shujing Xu, Nicholas Mancuso, Paul J. Newcombe, David V. Conti (2020). "A Hierarchical Approach Using Marginal Summary Statistics for Multiple Intermediates in a Mendelian Randomization or Transcriptome Analysis." <bioRxiv><doi:10.1101/2020.02.03.924241>.
| Version: | 1.0.0 |
| Imports: | ggplot2, ggpubr, dplyr, reshape2 |
| Suggests: | knitr, rmarkdown |
| Published: | 2020-02-20 |
| Author: | Lai Jiang |
| Maintainer: | Lai Jiang <jian848 at usc.edu> |
| BugReports: | https://github.com/lailylajiang/hJAM/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/lailylajiang/hJAM |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | hJAM results |
| Reference manual: | hJAM.pdf |
| Vignettes: |
hJAM vignette |
| Package source: | hJAM_1.0.0.tar.gz |
| Windows binaries: | r-devel: hJAM_1.0.0.zip, r-release: hJAM_1.0.0.zip, r-oldrel: hJAM_1.0.0.zip |
| macOS binaries: | r-release (arm64): hJAM_1.0.0.tgz, r-oldrel (arm64): hJAM_1.0.0.tgz, r-release (x86_64): hJAM_1.0.0.tgz, r-oldrel (x86_64): hJAM_1.0.0.tgz |
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These binaries (installable software) and packages are in development.
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