maskTracks-methods: maskTracks

In sheng-liu/sojourner: Statistical analysis of single molecule trajectories

Description

apply binary image masks to lists of track lists

Usage

maskTracks(folder, trackll)

filterOnCell(trackll, numTracks = 0)

sampleTracks(trackll, num = 0)

Arguments

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

Details

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.

Value

masked tracks in trackll format

Examples

#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)

sheng-liu/sojourner documentation built on April 2, 2021, 2:30 a.m.