Description Usage Arguments Details Value Author(s) See Also Examples
View source: R/landmarkMatrix.R
This functions first identifies high-density regions for each
flowFrame
in a
flowSet
and subsequently tries
to cluster these regions, yielding the landmarks matrix that needs to
be supplied to landmarkreg
. The function is
considered to be internal.
1 2 | landmarkMatrix(data, fres, parm, border=0.05, peakNr=NULL, densities =
NULL, n = 201, indices=FALSE)
|
data |
A |
fres |
A list of
|
parm |
Character scalar of flow paramater to compute landmarks for. |
border |
A numeric in |
peakNr |
Force a fixed number of peaks. |
densities |
An optional matrix of y values of the density
estimates for the |
n |
Number of bins used for the density estimation. |
indices |
Return matrix of population indices instead of landmark locations. These indices can be used to point into the populations identified by the curv1Filter. |
In order to normalize the data using the landmarkreg
function
in the fda
, a set of landmarks has to
be computed for each flowFrame
in a flowSet
. The number
of lansmarks has to be the same for each frame. This function
identifies high-density regions in each frame, computes a simple
clustering and returns a matrix of landmark locations. Missing
landmarks of individual frames are substituted by the mean landmark
location of the respective cluster.
A matrix of landmark locations. Columns are landmarks and rows are
flowFrames
.
Florian Hahne
1 2 3 4 | library(flowCore)
data(GvHD)
tmp <- list("FSC-H"=filter(GvHD[1:3], curv1Filter("FSC-H")))
res <- flowStats:::landmarkMatrix(GvHD[1:3], tmp, "FSC-H")
|
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