getGeneSimPrototypes: Compute functional similarity of genes with respect to a...

Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/geneSimilarity.R

Description

Computes the pairwise functional similarities for a list of genes: Each gene is represented by a feature vector containing the gene's similarities to predefined prototype genes.

Usage

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getGeneSimPrototypes(genelist, prototypes = NULL, similarity = "max",
                     similarityTerm = "JiangConrath", pca = TRUE,
                     normalization = TRUE, verbose = FALSE) 

Arguments

genelist

character vector of primary gene IDs according to organism annotation package (see setEvidenceLevel)

prototypes

character vector of Entrez gene IDs representing the prototypes

similarity

method to calculate the similarity to prototypes

similarityTerm

method to compute the GO term similarity

pca

perform PCA on feature vectors to reduce dimensionality

normalization

normalize similarities to [0,1]: sim(x,y) <- 0.5*(sim(x,y)/sqrt(sim(x,x)*sim(y,y)) + 1)

verbose

print additional information

Details

The method calls getGeneFeaturesPrototypes to calculate the feature vectors. The functional similarity between two genes is essentially given by the dot product between their feature vectors.

Value

List with items

"similarity"

n x n similarity matrix (n = number of genes)

"prototypes"

prototypes (= prinicipal components, if PCA has been performed)

"features"

feature vectors for each gene: n x d data matrix

Note

The result depends on the currently set ontology ("BP","MF","CC").

Author(s)

Holger Froehlich

References

[1] 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

[2] N. Speer, H. Froehlich, A. Zell, Functional Grouping of Genes Using Spectral Clustering and Gene Ontology, Proc. Int. Joint Conf. on Neural Networks (IJCNN), pp. 298 - 303, 2005

See Also

getGeneFeaturesPrototypes, selectPrototypes, getGeneSim, getTermSim, setOntology

Examples

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#\donttest{ may take some time ...
 proto=selectPrototypes(n=5) # --> returns a character vector of 5 genes with the highest number of annotations
 getGeneSimPrototypes(c("207","208"),prototypes=proto, similarityTerm="Resnik")
#}

GOSim documentation built on Nov. 1, 2018, 2:26 a.m.