limma
This is the development version of limma; for the stable release version, see limma.
Linear Models for Microarray Data
Bioconductor version: Development (3.18)
Data analysis, linear models and differential expression for microarray data.
Author: Gordon Smyth [cre,aut], Yifang Hu [ctb], Matthew Ritchie [ctb], Jeremy Silver [ctb], James Wettenhall [ctb], Davis McCarthy [ctb], Di Wu [ctb], Wei Shi [ctb], Belinda Phipson [ctb], Aaron Lun [ctb], Natalie Thorne [ctb], Alicia Oshlack [ctb], Carolyn de Graaf [ctb], Yunshun Chen [ctb], Mette Langaas [ctb], Egil Ferkingstad [ctb], Marcus Davy [ctb], Francois Pepin [ctb], Dongseok Choi [ctb]
Maintainer: Gordon Smyth <smyth at wehi.edu.au>
citation("limma")
):
Installation
To install this package, start R (version "4.3") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("limma")
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("limma")
A brief introduction to limma | HTML | R Script |
limma User's Guide | ||
Reference Manual | ||
NEWS | Text |
Details
biocViews | AlternativeSplicing, BatchEffect, Bayesian, BiomedicalInformatics, CellBiology, Cheminformatics, Clustering, DataImport, DifferentialExpression, DifferentialSplicing, Epigenetics, ExonArray, FunctionalGenomics, GeneExpression, GeneSetEnrichment, Genetics, ImmunoOncology, Metabolomics, MicroRNAArray, Microarray, MultipleComparison, Normalization, OneChannel, Preprocessing, ProprietaryPlatforms, Proteomics, QualityControl, RNASeq, Regression, Sequencing, Software, SystemsBiology, TimeCourse, Transcription, Transcriptomics, TwoChannel, mRNAMicroarray |
Version | 3.57.7 |
In Bioconductor since | BioC 1.6 (R-2.1) or earlier (> 18 years) |
License | GPL (>=2) |
Depends | R (>= 3.6.0) |
Imports | grDevices, graphics, stats, utils, methods, statmod |
Linking To | |
Suggests | BiasedUrn, ellipse, gplots, knitr, locfit, MASS, splines, affy, AnnotationDbi, Biobase, BiocStyle, GO.db, illuminaio, org.Hs.eg.db, vsn |
System Requirements | |
Enhances | |
URL | https://bioinf.wehi.edu.au/limma/ |
See More
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | limma_3.57.7.tar.gz |
Windows Binary | limma_3.57.7.zip |
macOS Binary (x86_64) | limma_3.57.7.tgz |
macOS Binary (arm64) | limma_3.57.7.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/limma |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/limma |
Bioc Package Browser | https://code.bioconductor.org/browse/limma/ |
Package Short Url | https://bioconductor.org/packages/limma/ |
Package Downloads Report | Download Stats |