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matlabcode/FCS/master_workflow_fit_dye.m

-function master_workflow_fit_dye
+function master_workflow_fit_dye(wd)
 % MASTER_WORKFLOW_FIT_DYE call workflow_fit_dye for several directorie
 % specified in the script
 % 
 % Antonio Politi, EMBL, January 2017
-
-wd = 'Z:\AntonioP_elltier1\CelllinesImaging\MitoSysPipelines';
-cd(wd);
+if nargin < 1
+    wd = uigetdir('.', 'Specify main directory where to search for Alexa dye folders');
+    
+    %wd = 'Z:\AntonioP_elltier1\CelllinesImaging\MitoSysPipelines';
+    cd(wd);
+end
 if ~exist(fullfile(wd, 'ProcessingHelpFiles'));
     mkdir(fullfile(wd, 'ProcessingHelpFiles'));
 end
@@ -26,4 +29,5 @@ for idir = 1:length(indirCell)
     indir = indirCell{idir};
     display(['master_workflow_fit_dye processing directory ' num2str(idir) ' ' indir])
     workflow_fit_dye(indir, kappaVal, outputdir, '1c');
+    
 end
\ No newline at end of file

matlabcode/FCS/testWriteresToSubfolder.m

+function main()
+%%
+resfile = 'Z:\AntonioP_elltier1\CelllinesImaging\MitoSysPipelines\161216_WAPLgfpc\MitoSys2\2c_proc_weight0.res';
+
+
+

matlabcode/FCS/workflow_fit_dye.m

 function [focVol] = workflow_fit_dye(indir, kappaVal, outputdir, FAsession)
 % COMPUTEDIRECTORY perform fitting of dye in a specific directory. program
-% assumes that traces of one experiment are all in one directory
+% assumes that traces of one experiment are all in one directory!
 %   INPUT:
 %       inidir   - directory where to extract files
 %       kappaVal - a vector of kappa values
@@ -161,7 +161,7 @@ else
             %% find best fit
             mNorm = mean(normN,2); % mean of normalized norms along experiments
             [val, pos] = min(mean(normN,2)); % find minimum at pos
-            kappa = kappaVal(pos);          % kappa value
+            kappa = kappaVal(pos);           % kappa value
         end
         %% Compute means from mean tauD1 and mean N. Using directly the data could increase error on focal volume (^3)
         for i = 1:lk
@@ -232,11 +232,10 @@ for iC = 1:2
     end
 end
 
-%% update xml files
+%% update xml files and write a res file
 if ~ZEN    
     for iD = 1:length(dataC)
         node = xmlFA.readnode(xmlFAfiles{iD});
-
         [path, fout, ext] = fileparts(xmlFAfiles{iD});
         fname_out = fullfile(path, [fout '_opt' ext]);
         idxs = MO.getDataIndexes(dataC{iD}, MO.tauBoundary);
@@ -261,6 +260,9 @@ if ~ZEN
         xmlFA.writenode(fname_out, node);
     end
 end
+
+
+
 %% plot results
 for iC = 1:2
     if (dataC{1}(1,iC*2) == 0) % do not process if channel has not been acquired

matlabcode/FCS/workflow_fit_protein.m

-function workflow_fit_protein(resfile, FAsession)
+function outfiles = workflow_fit_protein(resfile, FAsession)
 % WORKFLOW_FIT_PROTEIN perform fitting of protein data using as input a res file from FA 
 %   INPUT:
 %       resfile   - a result file containing the directory where to extract files
@@ -17,19 +17,33 @@ if nargin < 1
         return
     end
     resfile = fullfile(pathname, resfile);
+
 end
+[pathname, resbase, ext] = fileparts(resfile);
+flintfile = fullfile(pathname, [resbase '.fint']);
 
 if nargin < 2
     FAsession = '2c';
 end
 
+if ~exist(resfile)
+    display(['Could not find resfile' resfile]);
+end
+
 %% Initialization
 % load model class
 clear('MO');
 MO = proteinFcsmodel();
+
 % read FA result table
+if exist(flintfile)
+    flintT = readtable(flintfile,'Delimiter', '\t','FileType', 'text');
+else
+    flintT = [];
+end
 restable2c = readtable(resfile, 'Delimiter', '\t', 'Header', 1, 'FileType', 'text', 'TreatAsEmpty',{'NA'});
 restable1c = restable2c;
+
 % stat entries
 restable1c.P11Name = repmat({'pValueLRT'}, length(restable1c.P11Name),1);
 restable1c.P12Name = repmat({'pValueFtest'}, length(restable1c.P11Name),1);
@@ -40,8 +54,17 @@ restable2c.P11Name = repmat({'pValueLRT'}, length(restable1c.P11Name),1);
 restable2c.P12Name = repmat({'pValueFtest'}, length(restable1c.P11Name),1);
 restable2c.P13Name = repmat({'PAIC'}, length(restable1c.P11Name),1);
 restable2c.P14Name = repmat({'BIC'}, length(restable1c.P11Name),1);
-
-
+%% write fluorescence intensity to table
+if ~isempty(flintT)
+    restable1c.class = flintT.class;
+    restable2c.class = flintT.class;
+    for px = [1, 3, 5, 9];
+        for iCh = 1:2
+            restable1c(:,sprintf('flint%dCh%d', px, iCh)) = flintT(:, sprintf('Ch%d_%d_%d_',iCh, px, px));
+            restable2c(:,sprintf('flint%dCh%d', px, iCh)) = flintT(:, sprintf('Ch%d_%d_%d_',iCh, px, px));
+        end
+    end
+end
 
 %% this write empty entries as NaN (must double check afterwards in particular for annotation)
 
@@ -82,16 +105,6 @@ switch cond
         ZEN = 1;
 end
 
-%% define file prefix for images
-if ZEN
-    prefix = 'parZEN';
-else
-    prefix = 'parFAcorr';
-end
-
-if ~MO.weightChi2
-    prefix = [prefix '_unw'];
-end
 
 %% load data into cell array dataC
 display(['Load correlation data for ' resfile])
@@ -197,8 +210,10 @@ end
 %%
 tmpfiles = {fullfile(fileparts(resfile), ['1c_tmp.res']), ...
     fullfile(fileparts(resfile), ['2c_tmp.res'])};
-outfiles = {fullfile(fileparts(resfile), ['1c_proc_weight' num2str(MO.weightChi2) '.res']), ...
-    fullfile(fileparts(resfile), ['2c_proc_weight' num2str(MO.weightChi2) '.res'])};
+
+outfiles = {fullfile(fileparts(resfile), ['1c_opt' weightStr{MO.weightChi2+1} '.res']), ...
+    fullfile(fileparts(resfile), ['2c_opt' weightStr{MO.weightChi2+1} '.res'])};
+
 tables = {restable1c, restable2c};
 for ifile = 1:2
     writetable(tables{ifile}, tmpfiles{ifile},  'WriteVariableNames',false, 'Delimiter', '\t','FileType', 'text');
@@ -207,7 +222,12 @@ for ifile = 1:2
     fileout = fopen(outfiles{ifile}, 'w');
     for i = 1:2
         tline = fgetl(filepre);
-        fwrite( fileout, sprintf('%s\n', tline ) );
+        if i==2
+            % add extra column name for fluorescence intensity and class
+            str1 = strjoin(restable1c.Properties.VariableNames(170:end), '\t');
+            tline = strjoin({tline, str1}, '\t');
+        end
+        fwrite(fileout, sprintf('%s\n', tline ) );
     end
     fclose(filepre);
     fclose(fileout);