eigengenes: Create a module eigengene matrix

In dswatson/biomisc: Convenient wrappers for functions in bioinformatics analysis pipelines

Description

This function reduces an expression matrix to the module level.

Usage

eigengenes(dat, geneSets)

Arguments

dat	An expression matrix or matrix-like object, with rows corresponding to probes and columns to samples. Data is presumed to be filtered and normalized prior to dimensionality reduction. For count data, this means undergoing some sort of variance stabilizing transformation, such as lcpm, vst, or rlog.
geneSets	A named list of one or several gene sets.

Details

Eigengenes are a convenient way to summarize data from a given gene set into a single vector of length equal to the study sample size. The eigengene of a module represents the first principle component of the sample by probe expression matrix for all genes of which the module is composed. This is useful for correlating gene sets with one another, or associating them with clinical variables of interest. They may even be used to create a meta-network of module eigengenes.

References

Zhang, B. & Horvath, S. (2005). "A General Framework for Weighted Gene Co-Expression Network Analysis". Stat. Appl. Genet. Molec. Biol., 4: 1, 17. https://www.ncbi.nlm.nih.gov/pubmed/16646834

Langfelder, P. & Horvath, S. (2007). "Eigengene networks for studying the relationships between co-expression modules." BMC Bioinformatics, 1: 54. http://bmcsystbiol.biomedcentral.com/articles/10.1186/1752-0509-1-54

Horvath S. & Dong, J. (2008). "Geometric Interpretation of Gene Coexpression Network Analysis." PLoS Comput. Biol., 4(8): e1000117. http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000117

Examples

# Simulate data
mat <- matrix(rnorm(5000 * 10), nrow = 5000, ncol = 10)
grp <- rep(c("A", "B"), each = 5)
geneSets = list()
for (i in 0:10) {
  genes <- ((30 * i) + 1):(30 * (i + 1))
  mat[genes, grp == "A"] <- mat[genes, grp == "A"] + rnorm(1)
  geneSets[[paste("Set", i)]] <- genes
}

# Create eigengene matrix
eg_mat <- eigengenes(mat, geneSets)

dswatson/biomisc documentation built on May 15, 2019, 4:52 p.m.