genefu (version 2.4.2)

ovcCrijns: Function to compute the subtype scores and risk classifications for the prognostic signature published by Crinjs et al.

Description

This function computes subtype scores and risk classifications from gene expression values using teh weights published by Crijns et al.

Usage

ovcCrijns(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.

Details

Note that the original algorithm has not been implemented as it necessitates refitting of the model weights in each new dataset. However the current implementation should give similar results.

References

Crijns APG, Fehrmann RSN, de Jong S, Gerbens F, Meersma G J, Klip HG, Hollema H, Hofstra RMW, te Meerman GJ, de Vries EGE, van der Zee AGJ (2009) "Survival-Related Profile, Pathways, and Transcription Factors in Ovarian Cancer" PLoS Medicine, 6(2):e1000024.

See Also

sigOvcCrijns

Examples

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