ovcTCGA: Function to compute the prediction scores and risk...

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

Description

This function computes signature scores and risk classifications from gene expression values following the algorithm developed by the TCGA consortium for ovarian cancer.

Usage

ovcTCGA(data, annot, 
gmap = c("entrezgene", "ensembl_gene_id", "hgnc_symbol", "unigene"), 
do.mapping = FALSE, 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 one column named as gmap, dimnames being properly defined.
gmap	character string containing the biomaRt attribute to use for mapping if do.mapping=TRUE
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.
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.

Author(s)

Benjamin Haibe-Kains

References

Bell D, Berchuck A, Birrer M et al. (2011) "Integrated genomic analyses of ovarian carcinoma", Nature, 474(7353):609–615

See Also

sigOvcTCGA

Examples

## load the ovcTCGA signature
data(sigOvcTCGA)
## load NKI dataset
data(nkis)
colnames(annot.nkis)[is.element(colnames(annot.nkis), "EntrezGene.ID")] <- "entrezgene"
## compute relapse score
ovcTCGA.nkis <- ovcTCGA(data=data.nkis, annot=annot.nkis, gmap="entrezgene", do.mapping=TRUE)
table(ovcTCGA.nkis$risk)

genefu documentation built on Jan. 28, 2021, 2:01 a.m.