injectOutliers: Inject artificial outliers in an existing fds

In c-mertes/FRASER: Find RAre Splicing Events in RNA-Seq Data

Inject artificial outliers in an existing fds

Description

Inject artificial outliers in an existing fds

Usage

injectOutliers(
  fds,
  type = psiTypes,
  freq = 0.001,
  minDpsi = 0.2,
  minCoverage = 2,
  deltaDistr = "uniformDistr",
  verbose = FALSE,
  method = c("samplePSI", "meanPSI", "simulatedPSI"),
  BPPARAM = bpparam()
)

Arguments

fds	FraserDataSet
type	The psi type
freq	The injection frequency.
minDpsi	The minimal delta psi with which outliers will be injected.
minCoverage	The minimal total coverage (i.e. N) required for a junction to be considered for injection of an outlier.
deltaDistr	The distribution from which the delta psi value of the injections is drawn (default: uniform distribution).
verbose	Should additional information be printed during computation?
method	Defines by which method the new psi of injections is computed, i.e. to which value the delta psi of the injection is added: "meanPSI" for adding to the mean psi of the junction over all samples or "samplePSI" to add to the psi value of the junction in the specific sample. "simulatedPSI" is only possible if a simulated dataset is used.
BPPARAM	A BiocParallel object to run the computation in parallel

Value

FraserDataSet

Examples

# A generic dataset
fds <- makeSimulatedFraserDataSet()
fds <- calculatePSIValues(fds)
fds <- injectOutliers(fds, minDpsi=0.2, freq=1E-3)

c-mertes/FRASER documentation built on June 14, 2024, 7:49 p.m.