getSimScores {BrainSABER} | R Documentation

## Get Similarity Scoring for a Gene Expression Vector

### Description

This function computes the similarity score of a gene expression vector returned by `getExternalVector` or a trimmed data set returned by `getTrimmedExternalSet`, compared to a subset of AIBSARNA, obtained by `getRelevantGenes`.

### Usage

    getSimScores(data, relevantGenes = NULL, similarity_method = "cosine")

### Arguments

`data` | a named vector of gene expression values returned by `getExternalVector`, a SummarizedExperiment returned by `getTrimmedExternalSet`, or a CellScabbard object.
`relevantGenes` | a SummarizedExperiment object created using the `getRelevantGenes()` function
`similarity_method` | currently supported similarity methods are "cosine" and "euclidean", defaults to "cosine"

### Value

If `data` is a vector, returns a vector of similarity scores for each sample in relevantGenes. If `data` is a SummarizedExperiment, returns a data frame, with columns containing the similarity scores for and named after each sample in `data`, and rows named after each sample in `relevantGenes`. If `data` is a CellScabbard, the results will be stored in its similarityScores slot.

### Examples

    AIBSARNA <- buildAIBSARNA(mini = TRUE)
    # Example 1 - using CellScabbard class
    # get a random sample of 3 genes
    totalGenes <- nrow(AIBSARNA)
    gene_idx <- sample.int(totalGenes, 3)
    sample_idx <- c(1,3,5)
    # Subset AIBSARNA
    exprs <- assay(AIBSARNA)[gene_idx, sample_idx]
    fd <- rowData(AIBSARNA)[gene_idx, ]
    pd <- colData(AIBSARNA)[sample_idx, ]
    # build a trimmed data set
    myGenes <- CellScabbard(exprsData = exprs, phenoData = pd, featureData = fd,
                            AIBSARNA = AIBSARNA, autoTrim = TRUE)
    similarityScores(myGenes) <- getSimScores(data = myGenes,
                                              similarity_method = "cosine")
    similarityScores(myGenes)
    similarityScores(myGenes) <- getSimScores(data = myGenes,
                                              similarity_method = "euclidean")
    similarityScores(myGenes)

    # Example 2 - manual gene selection and relevant gene extraction
    myGenes <- c(4.484885, 0.121902, 0.510035)
    names(myGenes) <- c("TSPAN6", "DPM1", "C1orf112")
    myGeneSet <- getRelevantGenes(myGenes, AIBSARNA = AIBSARNA,
        AIBSARNAid = "gene_symbol")
    CosScores <- getSimScores(myGenes, myGeneSet,
        similarity_method = "cosine")
    EucScores <- getSimScores(myGenes, myGeneSet,
        similarity_method = "euclidean")

[Package BrainSABER version 1.0.0 Index]