results,FraserDataSet-method {FRASER} | R Documentation

## Extracting results and aberrant splicing events

### Description

The result function extracts the results from the given analysis object based on the given options and cutoffs. The aberrant function extracts aberrant splicing events based on the given cutoffs.

### Usage

    ## S4 method for signature 'FraserDataSet'
    results(
      object,
      sampleIDs = samples(object),
      padjCutoff = 0.05,
      zScoreCutoff = NA,
      deltaPsiCutoff = 0.3,
      minCount = 5,
      psiType = c("psi3", "psi5", "theta"),
      additionalColumns = NULL,
      BPPARAM = bpparam(),
      ...
    )

    resultsByGenes(res, geneColumn = "hgncSymbol", method = "BY")

    ## S4 method for signature 'FraserDataSet'
    aberrant(
      object,
      type = currentType(object),
      padjCutoff = 0.05,
      deltaPsiCutoff = 0.3,
      zScoreCutoff = NA,
      minCount = 5,
      by = c("none", "sample", "feature"),
      aggregate = FALSE,
      ...
    )

### Arguments

`object` | A `FraserDataSet` object
`sampleIDs` | A vector of sample IDs for which results should be retrieved
`padjCutoff` | The FDR cutoff to be applied or NA if not requested.
`zScoreCutoff` | The z-score cutoff to be applied or NA if not requested.
`deltaPsiCutoff` | The cutoff on delta psi or NA if not requested.
`minCount` | The minimum count value of the total coverage of an intron to be considered as significant. result
`psiType` | The psi types for which the results should be retrieved.
`additionalColumns` | Character vector containing the names of additional columns from mcols(fds) that should appear in the result table (e.g. ensembl_gene_id). Default is `NULL`, so no additional columns are included.
`BPPARAM` | The BiocParallel parameter.
`...` | Further arguments can be passed to the method. If "zscores", "padjVals" or "dPsi" is given, the values of those arguments are used to define the aberrant events.
`res` | Result as created with `results()`
`geneColumn` | The name of the column in `mcols(res)` that contains the gene symbols.
`method` | The p.adjust method that is being used to adjust p values per sample.
`type` | Splicing type (psi5, psi3 or theta)
`by` | By default `none` which means no grouping. But if `sample` or `feature` is specified the sum by sample or feature is returned
`aggregate` | If TRUE the returned object is based on the grouped features

### Value

For `results`: GRanges object containing significant results. For `aberrant`: Either a of logical values of size introns/genes x samples if "by" is NA or a vector with the number of aberrant events per sample or feature depending on the vaule of "by"

### Examples

    # get data, fit and compute p-values and z-scores
    fds <- createTestFraserDataSet()

    # extract results: for this example dataset, z score cutoff of 2 is used to
    # get at least one result and show the output
    res <- results(fds, padjCutoff=NA, zScoreCutoff=3, deltaPsiCutoff=0.05)
    res

    # aggregate the results by genes (gene symbols need to be annotated first
    # using annotateRanges() function)
    resultsByGenes(res)

    # get aberrant events per sample: on the example data, nothing is aberrant
    # based on the adjusted p-value
    aberrant(fds, type="psi5", by="sample")

    # get aberrant events per gene (first annotate gene symbols)
    fds <- annotateRangesWithTxDb(fds)
    aberrant(fds, type="psi5", by="feature", zScoreCutoff=2, padjCutoff=NA,
            aggregate=TRUE)

    # find aberrant junctions/splice sites
    aberrant(fds, type="psi5")

[Package FRASER version 1.4.0 Index]