getGeneSim {GOSim} | R Documentation |
Calculate the pairwise functional similarities for a list of genes using different strategies.
getGeneSim(genelist, similarity = "funSimMax", similarityTerm = "Lin", normalization = TRUE, method = "sqrt", avg = (similarity=="OA"), verbose = TRUE)
genelist |
character vector of Entrez gene IDs |
similarity |
method to calculate the functional similarity between gene products |
similarityTerm |
method to compute the similarity of GO terms |
normalization |
normalize similarities yes/no |
method |
"sqrt": normalize sim(x,y) <- sim(x,y)/sqrt(sim(x,x)*sim(y,y)); "Lin": normalize sim(x,y) <- 2*sim(x,y)/(sim(x,x) + sim(y,y)). NOTE: normalization does not have any effect, if similarity = "funSimMax", "funSimAvg" or similarity = "OA" and avg=TRUE |
avg |
standardize the OA kernel by the maximum number of GO terms for both genes |
verbose |
print out some information |
The method to calculate the pairwise functional similarity between gene products can either be:
n x n similarity matrix (n = number of genes)
The result depends on the currently set ontology.
Holger Froehlich
H. Froehlich, N. Speer, C. Spieth, and A. Zell, Kernel Based Functional Gene Grouping, Proc. Int. Joint Conf. on Neural Networks (IJCNN), 6886 - 6891, 2006.
A. Schlicker, F. Domingues, J. Rahnenfuehrer and Thomas Lengauer, A new measure for functional similarity of gene products based on Gene Ontology, BMC Bioinformatics, 7, 302, 2006.
getGeneSimPrototypes
, getTermSim
, setOntology
# see evaluateClustering