LIMMA:
Linear Models for Microarray Data
A software package for the analysis of gene expression microarray data, especially the use of linear models for analysing designed experiments and the assessment of differential expression.
The package includes pre-processing capabilities for two-colour spotted arrays.
The differential expression methods apply to all array platforms and treat Affymetrix, single channel
and two channel experiments in a unified way.
LIMMA is available as part of Bioconductor
project. To install from the R command line, type
> source("http://www.bioconductor.org/biocLite.R")
> biocLite("limma")
> biocLite("statmod")
Comprehensive documentation is distributed with the package. The
Limma User's Guide is also available as a link from the Bioconductor
limma
package page. Help using LIMMA can be obtained by sending questions or
problems to the Bioconductor mailing list
bioconductor@stat.math.ethz.ch.
Related Packages
LIMMA is a command driven package but menu driven interfaces are
also available. See
limmaGUI
for two-colour arays or
affylmGUI
for Affymetrix arrays.
Citing limma
Limma is an implementation of a body of methodological research
by the authors and co-workers. Please cite the appropriate
methodological papers when you use results from the software in a
publication. Such citations are the main means by which the authors
receive professional credit for their work.
If you use limma for differential expression analysis, using the
functions lmFit, eBayes, topTable
etc, please
cite:
Smyth, G. K. (2004). Linear models and empirical Bayes methods for
assessing differential expression in microarray experiments. Statistical
Applications in Genetics and Molecular Biology 3, No. 1, Article 3.
(Online,
Tech
Report PDF)
The normexp and other background correction features for two-colour
microarray data can be cited as
Ritchie, ME, Silver, J, Oshlack, A, Holmes, M, Diyagama,
D, Holloway, A, and Smyth, GK (2007). A comparison of background correction
methods for two-colour microarrays. Bioinformatics 23, 2700-2707. [Publisher Full Text]
[Supplementary
Information]
For normalization of two-colour microarray
data, please cite:
Smyth, G. K., and Speed, T. P. (2003). Normalization of cDNA microarray
data. Methods 31, 265-273. (PDF)
The above article describes the functions read.maimages,
normalizeWithinArrays, normalizeBetweenArrays
etc, including the use of spot quality weights.
If you use limma with duplicate spots or technical replication
using duplicateCorrelation, please cite
Smyth, G. K., Michaud, J., and Scott, H. (2005). The use of within-array
replicate spots for assessing differential expression in microarray
experiments. Bioinformatics 21(9), 2067-2075. (Supplementary
Information, Online,
PDF,
Errata)
If you estimate array quality weights using arrayWeights,
arrayWeightsSimple or arrayWeightsQuick, please
cite:
Ritchie, M. E., Diyagama, D., Neilson, J., van Laar, R., Dobrovic, A.,
Holloway, A., and Smyth, G. K. (2006). Empirical array quality weights for
microarray data. BMC Bioinformatics 7, 261. (Online, Supplementary
Information)
The limma software itself can be cited as:
Smyth, G. K. (2005). Limma: linear models for microarray data. In:
Bioinformatics and Computational Biology Solutions using R and Bioconductor,
R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W. Huber (eds.), Springer,
New York, pages 397-420. (Publisher web site,
PDF)
The above article describes the software package in the
context of the Bioconductor project and surveys the range of
experimental designs for which the package can be used, including
spot-specific dye-effects. The pre-processing capabilities of the
package are also described but more briefly, with examples of
background correction, spot quality weights and filtering with
control spots. This article is also the best current reference for
the normexp background correction
method.
Finally, if you are using one of the menu-driven interfaces to
the software, please cite the appropriate one of
Wettenhall, J. M., and Smyth, G. K. (2004). limmaGUI: a graphical user
interface for linear modeling of microarray data. Bioinformatics 20,
3705-3706. (Online)
Wettenhall, J. M., Simpson, K. M., Satterley, K., and Smyth, G.
K. (2006). affylmGUI: a graphical user interface for linear modeling of
single channel microarray data. Bioinformatics 22, 897 - 899.
(Online)
Archived copies of LIMMA for older versions of R
Links
The following are some projects which provide interfaces to the limma package.
Comments/Questions? Contact bioinf@wehi.edu.au.
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