GEM
GEM: fast association study for the interplay of Gene, Environment and Methylation
Bioconductor version: Release (3.20)
Tools for analyzing EWAS, methQTL and GxE genome widely.
Author: Hong Pan, Joanna D Holbrook, Neerja Karnani, Chee-Keong Kwoh
Maintainer: Hong Pan <pan_hong at sics.a-star.edu.sg>
Citation (from within R, enter
citation("GEM")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("GEM")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("GEM")
The GEM User's Guide | HTML | R Script |
Reference Manual | ||
NEWS | Text |
Details
biocViews | DNAMethylation, GUI, GeneExpression, GenomeWideAssociation, MethylSeq, MethylationArray, Regression, SNP, Software |
Version | 1.32.0 |
In Bioconductor since | BioC 3.4 (R-3.3) (8 years) |
License | Artistic-2.0 |
Depends | R (>= 3.3) |
Imports | tcltk, ggplot2, methods, stats, grDevices, graphics, utils |
System Requirements | |
URL |
See More
Suggests | knitr, RUnit, testthat, BiocGenerics, rmarkdown, markdown |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | GEM_1.32.0.tar.gz |
Windows Binary (x86_64) | GEM_1.32.0.zip (64-bit only) |
macOS Binary (x86_64) | GEM_1.32.0.tgz |
macOS Binary (arm64) | GEM_1.32.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/GEM |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/GEM |
Bioc Package Browser | https://code.bioconductor.org/browse/GEM/ |
Package Short Url | https://bioconductor.org/packages/GEM/ |
Package Downloads Report | Download Stats |