Perform normalizations on Normalyzer dataset

Usage

normMethods(
  nds,
  forceAll = FALSE,
  normalizeRetentionTime = TRUE,
  quiet = FALSE,
  rtStepSizeMinutes = 1,
  rtWindowMinCount = 100,
  rtWindowShifts = 1,
  rtWindowMergeMethod = "mean",
  noLogTransform = FALSE
)

Arguments

nds: Normalyzer dataset object.
forceAll: Force all methods to run despite not qualifying for thresholds.
normalizeRetentionTime: Perform retention time based normalization methods.
quiet: Prevent diagnostic output
rtStepSizeMinutes: Retention time normalization window size.
rtWindowMinCount: Minimum number of datapoints in each retention-time segment.
rtWindowShifts: Number of layered retention time normalized windows.
rtWindowMergeMethod: Merge approach for layered retention time windows.
noLogTransform: Per default NormalyzerDE performs a log-transformation on the input data. If not needed, specify this option

Value

Returns Normalyzer results object with performed analyzes assigned as attributes

Examples

data(example_summarized_experiment)
normObj <- getVerifiedNormalyzerObject("job_name", example_summarized_experiment)
#> Input data checked. All fields are valid.
#> Sample check: More than one sample group found
#> Sample replication check: All samples have replicates
#> RT annotation column found (5)
normResults <- normMethods(normObj)