View source: R/ovcAngiogenic.R
ovcAngiogenic | 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 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. |
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.
subtype: data frame reporting the subtype score, maximum likelihood classification and corresponding subtype probabilities.
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
sigOvcAngiogenic
# load the ovcAngiogenic signature
# 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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.