landmarkMatrix {flowStats} | R Documentation |
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.
landmarkMatrix(data, fres, parm, border=0.05, peakNr=NULL, densities = NULL, n = 201)
data |
A flowSet . |
fres |
A list of
filterResultList
objects generated by a filtering opration using a
curv1Filter . Each list
item represents the results for one of the flow parameters in
parm . |
parm |
Character scalar of flow paramater to compute landmarks for. |
border |
A numeric in [0,1] . Ignore all high-density
regions with mean values in the extreme percentiles of the data
range. |
peakNr |
Force a fixed number of peaks. |
densities |
An optional matrix of y values of the density
estimates for the flowSet . If this is not present, density
estimates will be calculated by the function. |
n |
Number of bins used for the density estimation. |
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
data(GvHD) tmp <- list("FSC-H"=filter(GvHD[1:3], curv1Filter("FSC-H"))) res <- flowStats:::landmarkMatrix(GvHD[1:3], tmp, "FSC-H")