limma: Linear Models for Microarray Data

Limma is an R 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. Limma provides the ability to analyse comparisons between many RNA targets simultaneously in arbitrary complicated designed experiments. Empirical Bayesian methods are used to provide stable results even when the number of arrays is small. The normalization and data analysis functions are for two-color spotted microarrays. The linear model and differential expression functions apply to all microarray technologies including Affymetrix and other single-channel oligonucleotide platforms. Limma is available on Bioconductor.

edgeR is an R package for analyzing sequence read count data from genomic sequencing technologies such as RNA-seq, ChIP-seq and ATAC-seq. Like limma, edgeR is particularly designed to detect genes or features that have changed abundance levels between experimental conditions or cell types. Whereas limma is designed to analyze continuous expression values, edgeR is designed to analyze abundance measured in terms of sequence read counts, which enables edgeR to be the underlying analysis engine for a wide range of sequencing technologies. Where limma uses linear models and normality, edgeR uses negative binomial generalized linear models. Like limma, edgeR has the ability to handle arbitrary experimental designs and to borrow information between genes or genomic features. edgeR is available on Bioconductor.

Bioconductor packages

limmaGUI

A Graphical User Interface for differential expression analysis of two-color microarray data using the limma package. limmaGUI is available on Bioconductor.

affylmGUI

affylmGUI provides a menu-driven interface to the affy, gcrma, affyPLM and limma packages for analysing Affymetrix microarray data. The package is developed by James Wettenhall and maintained by Keith Satterley, and available on Bioconductor.

goseq

goseq provides functional analysis of gene lists from RNA-Seq experiments, adjusting the gene length bias. The package is authored by Matt Young, and available on Bioconductor.

csaw

csaw performs differential binding analyses of ChIP-seq experiments. The package is authored by Aaron Lun. See the Bioconductor Newsletter article on An overview of the csaw package. The package is available on Bioconductor.

CRAN R packages

• statmod (2001–present) is an R package for biostatistical modelling, including REML analyses, Tweedie generalized linear models, comparative growth curve analysis, and limiting dilution analyses. The package is available on CRAN.

• dglm: Dougle generalized linear models. The package is maintained by Peter Dunn, and available on CRAN.

• tweedie: Functions for Tweedie distributions, exponential family distributions with power-variance functions. The package is maintained by Peter Dunn, and available on CRAN.

Web tools

• ELDA: Extreme limiting dilution analysis for comparing stem cell frequencies between populations.

• Compare Growth Curves. Permutation test for comparing groups of growth curves.