Select feature variables of interest — selectFeatureData • MSnbase

Select feature variables to be retained.

requiredFvarLabels returns a character vector with the required feature data variable names (fvarLabels, i.e. the column names in the fData data.frame) for the specified object.

selectFeatureData(object, graphics = TRUE, fcol)

requiredFvarLabels(x = c("OnDiskMSnExp", "MSnExp", "MSnSet"))

Arguments

object: An MSnSet, MSnExp or OnDiskMSnExp.
graphics: A logical (default is TRUE) indicating whether a shiny application should be used if available. Otherwise, a text menu is used. Ignored if k is not missing.
fcol: A numeric, logical or character of valid feature variables to be passed directly.
x: character(1) specifying the class name for which the required feature data variable names should be returned.

Value

For selectFeatureData: updated object containing only selected feature variables.

For requiredFvarLabels: character with the required feature variable names.

Author

Laurent Gatto

Examples


library("pRolocdata")
data(hyperLOPIT2015)
## 5 first feature variables
x <- selectFeatureData(hyperLOPIT2015, fcol = 1:5)
fvarLabels(x)
#> [1] "entry.name"          "protein.description" "peptides.rep1"      
#> [4] "peptides.rep2"       "psms.rep1"          
if (FALSE) {
## select via GUI
x <- selectFeatureData(hyperLOPIT2015)
fvarLabels(x)
}

## Subset the feature data of an OnDiskMSnExp object to the minimal
## required columns
f <- system.file("microtofq/MM14.mzML", package = "msdata")
od <- readMSData(f, mode = "onDisk")

## what columns do we have?
fvarLabels(od)
#>  [1] "fileIdx"                    "spIdx"                     
#>  [3] "smoothed"                   "seqNum"                    
#>  [5] "acquisitionNum"             "msLevel"                   
#>  [7] "polarity"                   "originalPeaksCount"        
#>  [9] "totIonCurrent"              "retentionTime"             
#> [11] "basePeakMZ"                 "basePeakIntensity"         
#> [13] "collisionEnergy"            "ionisationEnergy"          
#> [15] "lowMZ"                      "highMZ"                    
#> [17] "precursorScanNum"           "precursorMZ"               
#> [19] "precursorCharge"            "precursorIntensity"        
#> [21] "mergedScan"                 "mergedResultScanNum"       
#> [23] "mergedResultStartScanNum"   "mergedResultEndScanNum"    
#> [25] "injectionTime"              "filterString"              
#> [27] "spectrumId"                 "centroided"                
#> [29] "ionMobilityDriftTime"       "isolationWindowTargetMZ"   
#> [31] "isolationWindowLowerOffset" "isolationWindowUpperOffset"
#> [33] "scanWindowLowerLimit"       "scanWindowUpperLimit"      
#> [35] "spectrum"                  

## Reduce the feature data data.frame to the required columns only
od <- selectFeatureData(od, fcol = requiredFvarLabels(class(od)))
fvarLabels(od)
#> [1] "fileIdx"          "spIdx"            "acquisitionNum"   "retentionTime"   
#> [5] "msLevel"          "precursorScanNum"