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")

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