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Diffusion Simon Botrylloides Regeneration Group (master) Browse

SiBoRG/analysis/estimate_cell_concentration.m
3aa2120ee410master

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estimate_cell_concentration.m
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function [stats] = estimate_cell_concentration(files)
if iscell(files)
stats = cell(length(files),1);
for i=1:length(files)
stats{i} = estimate_cell_concentration(files{i});
end
stats = [files(:) stats];
return;
elseif (isdir(files))
content = dir(files);
newfiles = cell(length(content),1);
for i=1:length(content)
if content(i).name(1) ~= '.'
newfiles{i} = fullfile(files, content(i).name);
end
end
newfiles = newfiles(~cellfun('isempty', newfiles));
stats = [];
if numel(newfiles) > 0
stats = estimate_cell_concentration(newfiles);
end
return;
end
[dir, name, ext] = fileparts(files);
if (~strncmp(ext, '.fcs', 4))
stats = [];
return;
end
[r,h,d]=fca_readfcs(files);
startt = ((str2num(h.starttime(1:2))*60 + str2num(h.starttime(4:5)))*60 + str2num(h.starttime(7:8)))*1000 + str2num(h.starttime(10:11));
stopt = ((str2num(h.stoptime(1:2))*60 + str2num(h.stoptime(4:5)))*60 + str2num(h.stoptime(7:8)))*1000 + str2num(h.stoptime(10:11));
% Seems to yield second like this
hits = sort(r(:,end) / 10);
bins = [floor(min(hits)*0.95):ceil(max(hits)*1.05)];
[counts] = hist(hits, bins);
outliers = (counts < mean(counts)/3);
cleaned = counts(~outliers);
for nneigh = 5:5:15
F = ones(1,2*nneigh+1);
F = F/sum(F);
smoothed = conv(counts(1, :), F, 'same');
counts = [counts; smoothed];
smoothed = conv(cleaned(1, :), F, 'same');
cleaned = [cleaned; smoothed];
end
stats = cat(3,[mean(counts, 2) median(counts, 2), std(counts, 0, 2)], [mean(cleaned, 2) median(cleaned, 2), std(cleaned, 0, 2)]);
figure;plot(bins, counts);title(files);
figure;plot(bins(~outliers), cleaned);title(files);
%keyboard
return;
end
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