Function to compute the prediction scores and risk classifications for the ovarian cancer TCGA signature

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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

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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

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## 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)

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