maskTracks {sojourner} | R Documentation |
apply binary image masks to lists of track lists
maskTracks(folder, trackll) filterOnCell(trackll, numTracks = 0) sampleTracks(trackll, num = 0)
folder |
Full path to the output files. |
trackll |
A list of track lists. |
numTracks |
Minimum number of required tracks in the trackll |
num |
Number of tracks to randomly sample per trackl in trackll |
IMPORTANT: It will take an extremely long time to mask large datasets. Filter/trim first using filterTrack() and trimTrack(), then mask using maskTracks(folder, trackll)! Note the mask file should have the same name as the output files with a '_MASK.tif' ending. If there are more mask files than trackll, masking will fail. If there are less mask files, trackls without masks will be deleted. Users can use plotMask() and plotTrackOverlay() to see the mask and its effect on screening tracks.
filterOnCell() eliminates all trackl in trackll that has less than numTracks tracks.
sampleTracks() randomly samples num number of tracks for each trackl in trackll.
masked tracks in trackll format
#Basic masking with folder path with image masks folder = system.file('extdata','ImageJ',package='sojourner') trackll = createTrackll(folder=folder, input=3) trackll.masked <- maskTracks(folder = folder, trackll = trackll) #Compare the masking effect plotTrackOverlay(trackll) plotTrackOverlay(trackll.masked) #Plot mask mask.list=list.files(path=folder,pattern='_MASK.tif',full.names=TRUE) plotMask(folder) #If Nuclear image is available plotNucTrackOverlay(folder=folder,trackll=trackll) plotNucTrackOverlay(folder=folder,trackll=trackll.masked) #Plot mask plotMask(folder=folder)