EBarrays
Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification
Bioconductor version: Release (3.20)
EBarrays provides tools for the analysis of replicated/unreplicated microarray data.
Author: Ming Yuan, Michael Newton, Deepayan Sarkar and Christina Kendziorski
Maintainer: Ming Yuan <myuan at isye.gatech.edu>
Citation (from within R, enter
citation("EBarrays")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("EBarrays")
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("EBarrays")
Introduction to EBarrays | R Script | |
Reference Manual |
Details
biocViews | Clustering, DifferentialExpression, Software |
Version | 2.70.0 |
In Bioconductor since | BioC 1.6 (R-2.1) or earlier (> 19.5 years) |
License | GPL (>= 2) |
Depends | R (>= 1.8.0), Biobase, lattice, methods |
Imports | Biobase, cluster, graphics, grDevices, lattice, methods, stats |
System Requirements | |
URL |
See More
Suggests | |
Linking To | |
Enhances | |
Depends On Me | EBcoexpress, gaga, geNetClassifier |
Imports Me | casper |
Suggests Me | Category, dcanr |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | EBarrays_2.70.0.tar.gz |
Windows Binary (x86_64) | EBarrays_2.70.0.zip |
macOS Binary (x86_64) | EBarrays_2.70.0.tgz |
macOS Binary (arm64) | EBarrays_2.70.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/EBarrays |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/EBarrays |
Bioc Package Browser | https://code.bioconductor.org/browse/EBarrays/ |
Package Short Url | https://bioconductor.org/packages/EBarrays/ |
Package Downloads Report | Download Stats |