endoPredict {genefu} | R Documentation |
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.
endoPredict(data, annot, do.mapping = FALSE, mapping, verbose = FALSE)
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 |
|
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 |
|
The function works best if data have been noralized with MAS5. Note that for Affymetrix HGU datasets, the mapping is not necessary.
score |
Continuous signature scores |
risk |
Binary risk classification, |
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. |
Benjamin Haibe-Kains
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.
## 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)