Function to compute the subtype scores and risk classifications for the angiogenic molecular subtype in ovarian cancer

Description

This function computes subtype scores and risk classifications from gene expression values following the algorithm developed by Bentink, Haibe-Kains et al. to identify the angiogenic molecular subtype in ovarian cancer.

Usage

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ovcAngiogenic(data, annot, hgs, 
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.

hgs

vector of booleans with TRUE represents the ovarian cancer patients who have a high grade, late stage, serous tumor, FALSE otherwise. This is particularly important for properly rescaling the data. If hgs is missing, all the patients will be used to rescale the subtype score.

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.

subtype

data frame reporting the subtype score, maximum likelihood classification and corresponding subtype probabilities

Author(s)

Benjamin Haibe-Kains

References

Bentink S, Haibe-Kains B, Risch T, Fan J-B, Hirsch MS, Holton K, Rubio R, April C, Chen J, Wickham-Garcia E, Liu J, Culhane AC, Drapkin R, Quackenbush JF, Matulonis UA (2012) "Angiogenic mRNA and microRNA Gene Expression Signature Predicts a Novel Subtype of Serous Ovarian Cancer", PloS one, 7(2):e30269

See Also

sigOvcAngiogenic

Examples

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

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