These function extract the marker or unknown proteins into a new
MSnSet.
markerMSnSet(object, fcol = "markers")
unknownMSnSet(object, fcol = "markers")An instance of class MSnSet
The name of the feature data column, that will be used
to separate the markers from the proteins of unknown
localisation. When the markers are encoded as vectors, features of
unknown localisation are defined as fData(object)[, fcol] ==
"unknown". For matrix-encoded markers, unlabelled proteins are
defined as rowSums(fData(object)[, fcol]) == 0. Default is
"markers".
An new MSnSet with marker/unknown proteins only.
sampleMSnSet testMSnSet and
markers for markers encoding.
library("pRolocdata")
data(dunkley2006)
mrk <- markerMSnSet(dunkley2006)
unk <- unknownMSnSet(dunkley2006)
dim(dunkley2006)
#> [1] 689 16
dim(mrk)
#> [1] 261 16
dim(unk)
#> [1] 428 16
table(fData(dunkley2006)$markers)
#>
#> ER lumen ER membrane Golgi Mitochondrion PM
#> 14 45 28 55 46
#> Plastid Ribosome TGN unknown vacuole
#> 20 19 13 428 21
table(fData(mrk)$markers)
#>
#> ER lumen ER membrane Golgi Mitochondrion PM
#> 14 45 28 55 46
#> Plastid Ribosome TGN vacuole
#> 20 19 13 21
table(fData(unk)$markers)
#>
#> unknown
#> 428
## matrix-encoded markers
dunkley2006 <- mrkVecToMat(dunkley2006)
dim(markerMSnSet(dunkley2006, "Markers"))
#> [1] 261 16
stopifnot(all.equal(featureNames(markerMSnSet(dunkley2006, "Markers")),
featureNames(markerMSnSet(dunkley2006, "markers"))))
dim(unknownMSnSet(dunkley2006, "Markers"))
#> [1] 428 16
stopifnot(all.equal(featureNames(unknownMSnSet(dunkley2006, "Markers")),
featureNames(unknownMSnSet(dunkley2006, "markers"))))