getGeneFeaturesPrototypes {GOSim}R Documentation

Get feature vector representation of genes.

Description

Computes the feature vectors for list of genes: Each gene is represented by its similarities to predefined prototype genes.

Usage

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

Arguments

genelist character vector of Entrez gene IDs
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 scale the feature vectors to norm 1
verbose print out additional information

Details

If no prototypes are passed, the method calls the selectPrototypes function with no arguments. Hence, the prototypes in this case are the 250 genes with most known annotations.

The PCA postprocessing determines the principal components that can explain at least 95% of the total variance in the feature space.

The method to calculate the functional similarity of a gene to a certain prototype can either be

"max"
the maximum similarity between any two GO terms
"OA"
the optimal assignment (maximally weighted bipartite matching) of GO terms associated to the gene having fewer annotation to the GO terms of the other gene.

Value

List with items

"features" feature vectors for each gene: n x d data matrix
"prototypes" prototypes (= prinicipal components, if PCA has been performed)

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 newline [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

getGeneSimPrototypes, selectPrototypes, getGeneSim, getTermSim, setOntology

Examples

        # see selectPrototypes

[Package GOSim version 1.1.3.2 Index]