Description Usage Arguments Value Examples
This method computes the semantic similarity between samples annotated with different ontology terms from different ontologies
1 2 3 4 5 |
similarities |
a list of Similarity instances, one for each ontology used to annotate the data |
annotations |
a list of annotated data frames obtained using annotateDF or findEntities, one for each ontology |
sample1 |
the name of a sample in annotations |
sample2 |
the name of a sample in annotations |
aggregating_function |
A function used to aggregate the single similarities obtained from each ontology annotation. The function should be applied to a numeric vector. The default value is 'mean' |
The aggregate semantic similarity between the samples sample1 and sample2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | ef <- new('EntityFinder')
opts <- CMoptions()
cell_dict_file <- system.file('extdata', 'sample.cs.obo', package='OnassisJavaLibs')
sample_dict <- CMdictionary(cell_dict_file, outputDir=getwd(),
synonymType='ALL')
samples <- findEntities(ef, system.file('extdata', 'test_samples',
'test_samples.txt',
package='Onassis'), outDir=getwd(), multipleDocs=TRUE, configOpt=opts,
cmDict=sample_dict)
d_dict_file <- system.file('extdata', 'sample.do.obo', package='OnassisJavaLibs')
disease_dict <- CMdictionary(d_dict_file, outputDir=getwd(), synonymType='ALL')
disease <- findEntities(ef, system.file('extdata', 'test_samples',
'test_samples.txt', package='Onassis'),
multipleDocs=TRUE, outDir=getwd(), configOpt=opts,
cmDict=disease_dict)
cell_sim <- new('Similarity')
ontology(cell_sim) <- cell_dict_file
disease_sim <- new('Similarity')
ontology(disease_sim) <- d_dict_file
pairwiseConfig(cell_sim) <- listSimilarities()$pairwiseMeasures[9]
pairwiseConfig(disease_sim) <- listSimilarities()$pairwiseMeasures[9]
groupConfig(cell_sim) <- listSimilarities()$groupwiseMeasures[3]
groupConfig(disease_sim) <- listSimilarities()$groupwiseMeasures[3]
similarity <- multisim(list(cell_sim, disease_sim),
list(samples, disease),
as.character(as.vector(samples[1,1])),
as.character(as.vector(samples[5,1])), 'mean')
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.