gene70: Function to compute the 70 genes prognosis profile (GENE70)...

In bhklab/genefu: Computation of Gene Expression-Based Signatures in Breast Cancer

Function to compute the 70 genes prognosis profile (GENE70) as published by van't Veer et al. 2002

Description

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.

Usage

gene70(data, annot, do.mapping = FALSE, mapping,
  std = c("none", "scale", "robust"), 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.
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: scale for traditional standardization based on mean and standard deviation, robust for standardization based on the 0.025 and 0.975 quantiles, none to keep gene expressions unchanged.
verbose	TRUE to print informative messages, FALSE otherwise.

Value

A list with items:

• 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

References

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.

See Also

nkis

Examples

# 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)

bhklab/genefu documentation built on June 2, 2022, 2:56 p.m.