mrkVecToMat(object, vfcol = "markers", mfcol = "Markers")mrkMatToVec(object, mfcol = "Markers", vfcol = "markers")mrkMatAndVec(object, vfcol = "markers", mfcol = "Markers")showMrkMat(object, mfcol = "Markers")isMrkMat(object, fcol = "Markers")isMrkVec(object, fcol = "markers")mrkEncoding(object, fcol = "markers")
MSnSetwith a new vector (matrix) marker set.
factor, to be accurate), stored as feature metadata, and proteins of unknown or uncertain localisation (unlabelled, to be classified) are marked with the
"unknown"character. While very handy, this encoding suffers from some drawbacks, in particular the difficulty to label proteins that reside in multiple (possible or actual) localisations. The markers vector feature data is typically named
markers. A new matrix encoding is also supported. Each spatial compartment is defined in a column in a binary markers matrix and the resident proteins are encoded with 1s. The markers matrix feature data is typically named
Markers. If proteins are assigned unique localisations only (i.e. no multi-localisation) or their localisation is unknown (unlabelled), then both encodings are equivalent. 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.
mrkVecToMat functions enable the
conversion from matrix (vector) to vector (matrix). The
mrkMatAndVec function generates the missing encoding from
the existing one. If the destination encoding already exists, or,
more accurately, if the feature variable of the destination
encoding exists, an error is thrown. During the conversion from
matrix to vector, if multiple possible label exists, they are
dropped, i.e. they are converted to
isMrkMat can be used to test if a
marker set is encoded as a vector or a matrix.
"matrix" depending on the
nature of the markers.
markerMSnSet. To add markers to an existing
MSnSet, see the
pRolocmarkers, for a list of suggested markers.
library("pRolocdata") data(dunkley2006) dunk <- mrkVecToMat(dunkley2006) head(fData(dunk)$Markers) fData(dunk)$markers <- NULL dunk <- mrkMatToVec(dunk) stopifnot(all.equal(fData(dunkley2006)$markers, fData(dunk)$markers))
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