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hJAM: Hierarchical Joint Analysis of Marginal Summary Statistics

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
DOI: 10.32614/CRAN.package.hJAM
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

Documentation:

Reference manual: hJAM.pdf
Vignettes: hJAM vignette

Downloads:

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

Linking:

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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.