ggi: Function to compute the raw and scaled Gene expression Grade Index (GGI)

Description

This function computes signature scores and risk classifications from gene expression values following the algorithm used for the Gene expression Grade Index (GGI).

Usage

ggi(data, annot, do.mapping = FALSE, mapping, hg, 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.

Vector containing the histological grade (HG) status of breast cancer patients in the dataset.

verbose

TRUE to print informative messages, FALSE otherwise.

Value

scoreContinuous signature scores
riskBinary risk classification, 1 being high risk and 0 being low risk.
mappingMapping used if necessary.
probeIf mapping is performed, this matrix contains the correspondence between the gene list (aka signature) and gene expression data.

References

Sotiriou C, Wirapati P, Loi S, Harris A, Bergh J, Smeds J, Farmer P, Praz V, Haibe-Kains B, Lallemand F, Buyse M, Piccart MJ and Delorenzi M (2006) "Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis", Journal of National Cancer Institute, 98:262--272

Examples

Run this code

## load GGI signature
data(sig.ggi)
## load NKI dataset
data(nkis)
## compute relapse score
ggi.nkis <- ggi(data=data.nkis, annot=annot.nkis, do.mapping=TRUE,
  hg=demo.nkis[ ,"grade"])
table(ggi.nkis$risk)