limma pipeline

limma specifications


Unique identifier OMICS_00769
Name limma
Alternative names Linear Models for Microarray Data, r-bioc-limma
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 2.0
Computer skills Advanced
Version 3.24.15
Stability Stable
Requirements methods
Maintained Yes



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  • person_outline Gordon Smyth <>

Publication for Linear Models for Microarray Data

limma IN pipelines

PMCID: 5841087
PMID: 29545845
DOI: 10.3892/etm.2018.5833

[…] p-values of <0.05 and an absolute fc of >2 were considered to be degs. as shown in fig. 1, blue represents the data prior to correction and the middle line represents the median (fig. 1a). the limma data package was used to correct the original data (fig. 1b). the results showed that 153 genes between the sclc and the normal group (119 upregulated and 34 downregulated genes) differed […]

PMCID: 5856766
PMID: 29549264
DOI: 10.1038/s41467-018-03567-4

[…] and filtering for long non-coding genes and pairwise differential expression analysis performed in cuffdiff46. data from female mice were analyzed as per hodes et al. 5 whereby the voom47 and limma48 packages were utilized to generate differential expression signatures. for both sexes, differential expression comparisons were generated to compare the effects of esr1 overexpression […]

PMCID: 5891938
PMID: 29643944
DOI: 10.1186/s13148-018-0482-3

[…] channel: green; scan resolution = 3 μm; pmt: 100%, 20 bits). data were extracted with feature extraction software 10.7 (agilent technologies). raw data were normalized by the quantile algorithm of limma package in r. the raw data is available and deposited in public database (geo). the geo accession number is gse102897., hierarchical clustering was performed in mev_4_9_0 to identify […]

PMCID: 5206673
PMID: 28045093
DOI: 10.1038/srep39912

[…] intensity. the raw data were normalised and background was adjusted using the quantile algorithm within the r package marray. normalized data were analysed with a linear model for microarray data (limma), and a modified t test incorporates the benjamini-hochberg multiple hypotheses correction technique42. degs were identified based on fold changes and adjusted p values. a fold change threshold […]

PMCID: 5316826
PMID: 28193997
DOI: 10.1038/ncomms14127

[…] using agilent feature extraction software. all bioinformatics analyses were performed using r ( differential gene expression was determined using the r statistical package limma65. expression values were scaled per row by z-score (row average equals zero (white); positive or negative values indicate how many standard deviations the value is located above (red) […]

limma institution(s)
Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
limma funding source(s)
National Health and Medical Research Council Project Grant [1050661 and 1023454]; NHMRC Program Grant [1054618]; Victorian State Government Operational Infrastructure Support and Australian Government NHMRC IRIISS

limma review

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limma is a tool for reading, pre-processing, manipulate, quality control and analyse microarray data from a variety of different technologies. In my opinion, it could easily be considered the state-of-the-art tool for analysis of these kind of data. Linear modelling extended by limma provides a powerful way to analyse simple or complex experiments, allowing full control over covariates and time-series designs. Also, the team behind the tool made great effort in creating a tool easily accessible to non bio-statisticians, which is a plus in a lot of ways. Besides, I should also point out that limma has the capability to analyse RNA-seq experiments as well. Finally, users should definitely check the comprehensive (and well-written) limma User Guide, a document that will provide all the basics to get things rolling with the package.