ggi | R Documentation |
This function computes signature scores and risk classifications from gene expression values following the algorithm used for the Gene expression Grade Index (GGI).
ggi(data, annot, do.mapping = FALSE, mapping, hg, verbose = FALSE)
data |
Matrix of gene expressions with samples in rows and probes in columns, dimnames being properly defined. |
annot |
Matrix of annotations with at least one column named "EntrezGene.ID", dimnames being properly defined. |
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. |
mapping |
Matrix with columns "EntrezGene.ID" and "probe" used to force the mapping such that the probes are not selected based on their variance. |
hg |
Vector containing the histological grade (HG) status of breast cancer patients in the dataset. |
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.
Sotiriou C, Wirapati P, Loi S, Harris A, Bergh J, Smeds J, Farmer P, Praz V, Haibe-Kains B, Lallemand F, Buyse M, Piccart MJ and Delorenzi M (2006) "Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis", Journal of National Cancer Institute, 98:262–272
gene76
# load GGI signature data(sig.ggi) # load NKI dataset data(nkis) # compute relapse score ggi.nkis <- ggi(data=data.nkis, annot=annot.nkis, do.mapping=TRUE, hg=demo.nkis[ ,"grade"]) table(ggi.nkis$risk)
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