filterByMissingTimepoints: Filter proteins/peptides by the amount of measurements...
In pulsedSilac: Analysis of pulsed-SILAC quantitative proteomics data

Description Usage Arguments Value Examples

Searches for proteins/peptides that are not found in all timepoints. This can be done for each condition independently (strict = FALSE) or shared across conditions (strict = TRUE).

filterByMissingTimepoints(x, ...)

## S4 method for signature 'SilacProteinExperiment'
filterByMissingTimepoints(
  x,
  assayName,
  maxMissing = 0,
  strict = TRUE,
  conditionCol,
  returnVector = FALSE
)

## S4 method for signature 'SilacPeptideExperiment'
filterByMissingTimepoints(
  x,
  assayName,
  maxMissing = 0,
  strict = TRUE,
  conditionCol,
  returnVector = FALSE
)

## S4 method for signature 'SilacProteomicsExperiment'
filterByMissingTimepoints(
  x,
  assayName,
  maxMissing = 0,
  strict = TRUE,
  conditionCol,
  returnVector = FALSE
)

`x`	A `SilacProteinExperiment`, `SilacPeptideExperiment` or a `SilacProteomicsExperiment` object.
`...`	Unused.
`assayName`	A character indicating which assay will be used to count the number of missed timepoints.
`maxMissing`	A numeric indicating how many timepoints are allowed to be missed.
`strict`	Logical: if TRUE, then proteins have to meet the maxMissing criteria in all conditions and time replicates to pass; if FALSE then proteins only have to meet the maxMissing criteria in one condition or time replicate to pass.
`conditionCol`	A `character`, which indicates the column name in colData(x) that defines the different experiment conditions.
`returnVector`	Logical: if TRUE then a vector with the positions to be subset is returned.

A SilacProteinExperiment, SilacPeptideExperiment or a SilacProteomicsExperiment object or a logical vector with the rows that pass the minimum number of desired timepoints.

data('wormsPE')
filterByMissingTimepoints(wormsPE,
                          assayName = 'ratio',
                          maxMissing = 2,
                          strict = FALSE)