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hJAM  

Hierarchical Joint Analysis of Marginal Summary Statistics
View on CRAN: Click here


Download and install hJAM package within the R console
Install from CRAN:
install.packages("hJAM")

Install from Github:
library("remotes")
install_github("cran/hJAM")

Install by package version:
library("remotes")
install_version("hJAM", "1.0.0")



Attach the package and use:
library("hJAM")
Maintained by
Lai Jiang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-02-20
Latest Update: 2020-02-20
Description:
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." .
How to cite:
Lai Jiang (2020). hJAM: Hierarchical Joint Analysis of Marginal Summary Statistics. R package version 1.0.0, https://cran.r-project.org/web/packages/hJAM. Accessed 07 Mar. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited hJAM R package
View hJAM citation profile
Other R packages that hJAM depends, imports, suggests or enhances
Complete documentation for hJAM
Functions, R codes and Examples using the hJAM R package
Some associated functions: Gl . SNPs_heatmap . SNPs_info . SNPs_scatter_plot . betas.Gy . conditional_A . get_cond_A . get_cond_alpha . hJAM_egger . hJAM_lnreg . marginal_A . output.format . print.hJAM_egger . print.hJAM_lnreg . 
Some associated R codes: SNPs_heatmap.R . SNPs_scatter_plot.R . data.R . get_cond_A.R . hJAM_egger.R . hJAM_lnreg.R . print.R .  Full hJAM package functions and examples
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