genefu (version 2.4.2)

endoPredict: Function to compute the endoPredict signature as published by Filipits et al 2011

Description

This function computes signature scores and risk classifications from gene expression values following the algorithm used for the endoPredict signature as published by Filipits et al 2011.

Usage

endoPredict(data, annot, do.mapping = FALSE, mapping, verbose = FALSE)

Arguments

data

Matrix of gene expressions with samples in rows and probes in columns, dimnames being properly defined.

annot

Matrix of annotations with at least one column named "EntrezGene.ID", dimnames being properly defined.

do.mapping

TRUE if the mapping through Entrez Gene ids must be performed (in case of ambiguities, the most variant probe is kept for each gene), FALSE otherwise. Note that for Affymetrix HGU datasets, the mapping is not necessary.

mapping

Matrix with columns "EntrezGene.ID" and "probe" used to force the mapping such that the probes are not selected based on their variance.

verbose

TRUE to print informative messages, FALSE otherwise.

Value

• score
  Continuous signature scores
• risk
  Binary risk classification, 1 being high risk and 0 being low risk.
• mapping
  Mapping used if necessary.
• probe
  If mapping is performed, this matrix contains the correspondence between the gene list (aka signature) and gene expression data.

Details

The function works best if data have been noralized with MAS5. Note that for Affymetrix HGU datasets, the mapping is not necessary.

References

ilipits, M., Rudas, M., Jakesz, R., Dubsky, P., Fitzal, F., Singer, C. F., et al. (2011). "A new molecular predictor of distant recurrence in ER-positive, HER2-negative breast cancer adds independent information to conventional clinical risk factors." Clinical Cancer Research, 17(18):6012--6020.

Examples

## load GENE70 signature
data(sig.endoPredict)
## load NKI dataset
data(vdxs)
## compute relapse score
rs.vdxs <- endoPredict(data=data.vdxs, annot=annot.vdxs, do.mapping=FALSE)