samplesim {Onassis} | R Documentation

## `samplesim`

### Description

This method computes the semantic similarity between two named samples annotated with a group of ontolgy terms belonging to the same ontology

### Usage

    samplesim(object, sample1, sample2, annotated_df)

    ## S4 method for signature 'Similarity,character,character,data.frame'
    samplesim(object,
      sample1, sample2, annotated_df)

### Arguments

`object` | instance of class `Similarity-class`
`sample1` | A sample ID with its annotations available in a data frame
`sample2` | A sample ID with its annotations available in a data frame
`annotated_df` | data frame with annotations obtained using entityFinder. The data frame should have at least a column named 'sample_id' with the sample identifier and a column named 'term_url' with the URL of the ontology terms annotating the sample. The ontology terms must belong to the ontology loaded in the Similarity class.

### Value

The semantic similarity between the samples sample1 and sample2

### Examples

    sim <- new('Similarity')

    pairwiseConfig(sim) <- listSimilarities()$pairwiseMeasures[9]
    groupConfig(sim) <- listSimilarities()$groupwiseMeasures[3]
    ef <- new('EntityFinder')
    opts <- CMoptions()
    obo <- system.file('extdata', 'sample.cs.obo', package='OnassisJavaLibs')
    ontology(sim) <- obo
    sample_dict <- CMdictionary(inputFileOrDb=obo, outputDir=getwd(), synonymType='ALL')
    sra_chip_seq <- readRDS(system.file('extdata', 'vignette_data', 'GEO_human_chip.rds',
      package='Onassis'))
    chipseq_dict_annot <- EntityFinder(sra_chip_seq[1:20,c('sample_accession', 'title',
     'experiment_attribute', 'sample_attribute', 'description')], dictionary=sample_dict,
      options=opts)
    s <- samplesim(sim, as.character(as.vector(chipseq_dict_annot$sample_id[1])),
    as.character(as.vector(chipseq_dict_annot$sample_id[7])) , chipseq_dict_annot)

[Package Onassis version 1.6.1 Index]