labelStartAndEndFluoCells.m

Description: Takes in the procTracks data structure and two manually specified channel indices, and splits tracks based on the ratio of fluorescence in the two channels. Assumes that there are two populations in the dataset, each labelled in a separate channel.

Author: Oliver J. Meacock

labelStartAndEndFluoCells.m

%Classifies FAST tracks according to the fluoresence intensity measured in
%an initial and a final frame.
%
%Author: Oliver J. Meacock
 
clear all
close all
 
Root = 'D:\pilG_YFP_WT_CFP_Low_Density_Coculture';
trackLoc = [Root,filesep,'Tracks.mat']; %Location of your Tracks .mat file (containing procTracks)
startImgLoc = [Root,filesep,'PreSnap_YFP.tif']; %Location of the fluorescence image you took prior to timecourse imaging
endImgLoc = [Root,filesep,'PostSnap_YFP.tif']; %Location of the fluorescence image you took after timecourse imaging
 
load(trackLoc,'procTracks','trackSettings')
 
imgInfo = imfinfo(startImgLoc);
pixelSize = 1/imgInfo.XResolution; %As some upsampling may have occured during FAST processing, best to use resolution of fluoresence image
 
prePlane = double(imread(startImgLoc,'Index',1));
postPlane = double(imread(endImgLoc,'Index',1));
 
meanFluo = nan(size(procTracks,2),1);
 
%For each track...
for i = 1:length(procTracks)
    %If this track is present at the initial timepoint
    if procTracks(i).times(1) == 1
        [meanFluo(i),~] = meanIntInEllipse(prePlane,procTracks(i),1,pixelSize);
    elseif procTracks(i).times(end) == trackSettings.maxF
        [meanFluo(i),~] = meanIntInEllipse(postPlane,procTracks(i),size(procTracks(i).times,1),pixelSize);
    end
end
 
%Fit Gaussian mixture model of average intensities within ellipses to
%find threshold to split fluorescent from non-fluorescent cells
model = fitgmdist(meanFluo,2);
idx = cluster(model,meanFluo);
 
for i = 1:length(procTracks)
    if isnan(idx(i))
        procTracks(i).population = 3;
    elseif idx(i) == 1
        procTracks(i).population = 1;
    elseif idx(i) == 2
        procTracks(i).population = 2;
    end
end
 
save(trackLoc,'procTracks','-append')

Example output: Plot generated in the plotting module, showing how the two fluorescence channels are split into two separately labelled clusters: