ovcYoshihara: Function to compute the subtype scores and risk...

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

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

Description

This function computes subtype scores and risk classifications from gene expression values following the algorithm developed by Yoshihara et al, for prognosis in ovarian cancer.

Usage

ovcYoshihara(data, annot, hgs,
  gmap = c("entrezgene", "ensembl_gene_id", "hgnc_symbol", "unigene", "refseq_mrna"),
  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

A list with items:

• 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.

References

Yoshihara K, Tajima A, Yahata T, Kodama S, Fujiwara H, Suzuki M, Onishi Y, Hatae M, Sueyoshi K, Fujiwara H, Kudo, Yoshiki, Kotera K, Masuzaki H, Tashiro H, Katabuchi H, Inoue I, Tanaka K (2010) "Gene expression profile for predicting survival in advanced-stage serous ovarian cancer across two independent datasets", PloS one, 5(3):e9615.

See Also

sigOvcYoshihara

Examples

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

bhklab/genefu documentation built on June 2, 2022, 2:56 p.m.