gene70 {genefu} | R Documentation |
This function computes signature scores and risk classifications from gene expression values following the algorithm used for the 70 genes prognosis profile (GENE70) as published by van't Veer et al. 2002.
gene70(data, annot, do.mapping = FALSE, mapping, std = c("none", "scale", "robust"), 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. |
std |
Standardization of gene expressions: |
verbose |
|
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
L. J. van't Veer and H. Dai and M. J. van de Vijver and Y. D. He and A. A. Hart and M. Mao and H. L. Peterse and K. van der Kooy and M. J. Marton and A. T. Witteveen and G. J. Schreiber and R. M. Kerkhiven and C. Roberts and P. S. Linsley and R. Bernards and S. H. Friend (2002) "Gene Expression Profiling Predicts Clinical Outcome of Breast Cancer", Nature, 415:530–536.
## load GENE70 signature data(sig.gene70) ## load NKI dataset data(nkis) ## compute relapse score rs.nkis <- gene70(data=data.nkis) table(rs.nkis$risk) ## note that the discrepancies compared to the original publication ## are closed to the official cutoff, raising doubts on its exact value. ## computation of the signature scores on a different microarray platform ## load VDX dataset data(vdxs) ## compute relapse score rs.vdxs <- gene70(data=data.vdxs, annot=annot.vdxs, do.mapping=TRUE) table(rs.vdxs$risk)