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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 + fileLICENSE
URL:	https://github.com/lailylajiang/hJAM
NeedsCompilation:	no
Materials:	README
CRAN checks:	hJAM results

Documentation:

Reference manual:	hJAM.html ,hJAM.pdf
Vignettes:	hJAM vignette (source,R code)

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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