ovcAngiogenic {genefu} | R Documentation |
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.
ovcAngiogenic(data, annot, hgs, gmap = c("entrezgene", "ensembl_gene_id", "hgnc_symbol", "unigene"), do.mapping = FALSE, verbose = FALSE)
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 |
gmap |
character string containing the |
do.mapping |
|
verbose |
|
score |
Continuous signature scores |
risk |
Binary risk classification, |
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 |
Benjamin Haibe-Kains
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
## 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)