graph (version 1.50.0)

runClipperMulti: Run a topological analysis on an expression dataset using clipper.

Description

This function is deprecated and will be removed in a future release. You can use runClipper instead.

Usage

runClipperMulti(pathways, expr, classes, method, maxNodes=150, ...)

Arguments

pathways

a PathwayList object.

expr

a matrix (size: number p of genes x number n of samples) of gene expression.

classes

a vector (length: n) of class assignments.

method

the kind of test to perform on the cliques. It could be either "mean" or "variance".

maxNodes

ignore a pathway when it has more than this number of nodes.

...

Additional options; see for details easyClip.

Value

• A list with two elements:
  • results
  : a list with one entry for each successfully analyzed pathway;
• errors
• : a vector containing the error messages of failed analyses.

Details

The expression data and the pathway have to be annotated in the same set of identifiers.

References

Martini P, Sales G, Massa MS, Chiogna M, Romualdi C. Along signal paths: an empirical gene set approach exploiting pathway topology. Nucleic Acids Res. 2013 Jan 7;41(1):e19. doi: 10.1093/nar/gks866. Epub 2012 Sep 21. PubMed PMID: 23002139; PubMed Central PMCID: PMC3592432.

See Also

clipper

Examples

if (require(clipper) & require(ALL)){
  k <- pathways("hsapiens", "kegg")
  paths <- convertIdentifiers(k[1:5], "entrez")
  genes <- unlist(lapply(paths, nodes))
  data(ALL)
  all <- as.matrix(exprs(ALL[1:length(genes),1:20]))
  classes <- c(rep(1,10), rep(2,10))
  rownames(all) <- genes
  runClipperMulti(paths, all, classes, "mean", pathThr=0.1)
}