ovcTCGA | R Documentation |
This function computes signature scores and risk classifications from gene expression values following the algorithm developed by the TCGA consortium for ovarian cancer.
ovcTCGA(data, annot, 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. |
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.
Bell D, Berchuck A, Birrer M et al. (2011) "Integrated genomic analyses of ovarian carcinoma", Nature, 474(7353):609-615
sigOvcTCGA
# load the ovcTCGA signature data(sigOvcTCGA) # load NKI dataset data(nkis) colnames(annot.nkis)[is.element(colnames(annot.nkis), "EntrezGene.ID")] <- "entrezgene" # compute relapse score ovcTCGA.nkis <- ovcTCGA(data=data.nkis, annot=annot.nkis, gmap="entrezgene", do.mapping=TRUE) table(ovcTCGA.nkis$risk)
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