Added the plotting of the individual datapoints for the phosphoproteome

PlotFigures_phosphoproteome.m

@@ -24,7 +24,7 @@
     %% Plot supplemental timeseries
     disp('Plotting diabetes time series for the first 5 layers.')
     load('Results/layer6.mat','x', 'list','expData','structure','parameters') % Note: the second added layer is empty, therefore the fifth layer correspond to the saved layer6.
-    list.ExpansionIteration(list.ExpansionIteration>2) = list.ExpansionIteration(list.ExpansionIteration>2)-1; % Adjust the layer names since layer 2 is empty
+    list = RemoveEmptyLayers(list);
     modelName='layer5';
     disp('Starting to build the model file.')
     GenerateModel(structure,modelName,pwd,100);
@@ -44,6 +44,7 @@
     if plotSupplemental
         disp('Plotting all supplemental figures. This might take a while. ')
         load('Results/DataDriven.mat','x', 'list','expData','structure','parameters') % Load to restart the algorithm from this point later on if necessary
+        list = RemoveEmptyLayers(list);
         modelName='FinalExpandedModel';
         GenerateModel(structure,modelName,pwd,100);
         IQMmakeMEXmodel(IQMmodel([modelName '.txt']))
@@ -63,4 +64,15 @@
     cd(cwd)
     rethrow(err)
 end
+end
+
+function [list] = RemoveEmptyLayers(list)
+
+layers = list.ExpansionIteration;
+maxlayer = max(layers(~isinf(layers)));
+emptyLayers = find(~ismember(1:maxlayer, layers));
+for i =1:length(layers)
+    layers(i) = layers(i)-sum(emptyLayers<layers(i));
+end
+list.ExpansionIteration = layers;
 end

phosphoproteome scripts/InhibitionsForAllLayers.m

@@ -1,6 +1,6 @@
 function []=InhibitionsForAllLayers(coreModel)
 
-choice = input('Do you want to rerun the calculations, or only plot the figure? \nRerunning the calculations will be slow. \nOnly plot? \nPress ctrl+C to cancel \n(y/n):  ', 's');
+choice = input('Do you want to rerun the calculations, or only plot the figure? \nRerunning the calculations will be slow. \nOnly plot? \nPress ctrl+C to cancel \n(Y/n):  ', 's');
 if lower(choice)=='n'
     files = [dir('Results/empty*'); dir('Results/layer*')];
     layers=double(regexprep(string({files.name}),{'[a-zA-Z\.]'},{''}));
@@ -27,7 +27,7 @@
     disp('Calculating prediction accuracy for each layer, this may take a while')
 
     for i = 1:length(files)
-        fprintf('Done with %i of %i layers\n', i, length(files))
+        fprintf('\nCalculating accuracy for layer %i (of %i layers)\n\n', i, length(files))
         try
             load([files(i).folder '/' files(i).name],'list','expData','structure','parameters', 'layer', 'rel', 'layerStructure')
 
@@ -189,7 +189,7 @@
 % yticks((0:5)*10+50)
 yticks(0:25:100)
 xt = ((0:4)*ceil(((max(direction_MK.Layer)-min(direction_MK.Layer))/6)/10)*10+ceil(min(direction_MK.Layer)/10)*10);
-xticks([min(direction_MK.Layer) xt max(direction_MK.Layer)])
+xticks(unique([min(direction_MK.Layer) xt max(direction_MK.Layer)]))
 box off
 set(gca, 'FontSize',20)
 
@@ -235,7 +235,7 @@
 axis([direction_LY.Layer(1), direction_LY.Layer(end), ylower,100])
 yticks(0:25:100)
 xt = ((0:4)*ceil(((max(direction_LY.Layer)-min(direction_LY.Layer))/6)/10)*10+ceil(min(direction_LY.Layer)/10)*10);
-xticks([min(direction_LY.Layer) xt max(direction_LY.Layer)])
+xticks(unique([min(direction_LY.Layer) xt max(direction_LY.Layer)]))
 box off
 set(gca, 'FontSize',20)
 
@@ -257,7 +257,7 @@
 set(gca, 'FontSize',20)
 axis([direction_LY.Layer(1), direction_LY.Layer(end), 0.5, maxAdditions])
 xt = ((0:4)*ceil(((max(direction_LY.Layer)-min(direction_LY.Layer))/6)/10)*10+ceil(min(direction_LY.Layer)/10)*10);
-xticks([min(direction_LY.Layer) xt max(direction_LY.Layer)])
+xticks(unique([min(direction_LY.Layer) xt max(direction_LY.Layer)]))
 yticks(10.^(0:3))
 
 %%% PLOT LEGENDS
@@ -286,7 +286,7 @@
 
 axis([direction_LY.Layer(1), direction_LY.Layer(end), ylower,100])
 xt = ((0:4)*ceil(((max(direction_LY.Layer)-min(direction_LY.Layer))/6)/10)*10+ceil(min(direction_LY.Layer)/10)*10);
-xticks([min(direction_LY.Layer) xt max(direction_LY.Layer)])
+xticks(unique([min(direction_LY.Layer) xt max(direction_LY.Layer)]))
 
 title('Legend for layer')
 

phosphoproteome scripts/PlotFinalModel.m

@@ -134,10 +134,15 @@
         interactions(interactions.Tested~=min(interactions.Tested),:)=[]; %Remove all tested, not best, interactions
         layer = unique(interactions.ExpansionIteration);
         maxLayer=max(list.ExpansionIteration(list.Tested<chi2inv(0.95,length(time)-1))); % only works if loading the final layer
-        if maxLayer==5
-            maxLayer = 77; % To manage the colors if only plotting the first
+        if maxLayer<15
+            formatFig9 = true;
+            maxLayer = 57; % To manage the colors if only plotting the first
+        else
+            formatFig9 = false;
         end
         data=expData(ismember(expData.Genenamesprimary,protein),:);
+
+
         data.simulatedValues=data.simulatedValues/data.simulatedValues(1);
 
         cost=sum((data.meanValues-normalSim.statevalues(ismember(normalSim.time,time),i)').^2./data.SEMValues.^2);
@@ -170,7 +175,7 @@
             PlotSims(protein, layer, maxLayer, time, data, normTime,normVal,[],[], [],'', titleStr); % plot normal
         end
         if plotDiabetes
-            PlotSims(protein, layer, maxLayer, time, data, normTime,normVal,diabTime,diabVal, [],'', titleStr); % plot diabetes
+            PlotSims(protein, layer, maxLayer, time, data, normTime,normVal,diabTime,diabVal, [],'', titleStr, formatFig9); % plot diabetes
         end
         if plotInhib
             type.type='MK';
@@ -193,7 +198,8 @@
 end
 end
 
-function [] = PlotSims(protein, layer, maxLayer, time, data, normTime,normVal,diabTime,diabVal, inhibSim, inhibType, titleStr)
+function [] = PlotSims(protein, layer, maxLayer, time, data, normTime,normVal,diabTime,diabVal, inhibSim, inhibType, titleStr, formatFig9)
+if nargin <13, formatFig9=false; end
 clf
 
 colorNorm = [2 64 167]/256;
@@ -226,24 +232,32 @@
         value=data.meanValues(1,ismember(time,20))*(data.MKMean);
         upper=data.meanValues(1,ismember(time,20))*(data.MKMean+data.MKSEM);
         lower=data.meanValues(1,ismember(time,20))*(data.MKMean-data.MKSEM);
+        plot(20, data.meanValues(1,ismember(time,20)).*data.MKExpInsulin, 'o','MarkerSize',5,'linewidth', 1.5,'Color',colorInhib, 'MarkerFaceColor','None')
     elseif strcmp(inhibType.type,'LY')
         value=data.meanValues(1,ismember(time,20))*(data.LYMean);
         upper=data.meanValues(1,ismember(time,20))*(data.LYMean+data.LYSEM);
         lower=data.meanValues(1,ismember(time,20))*(data.LYMean-data.LYSEM);
+        plot(20, data.meanValues(1,ismember(time,20)).*data.LYExpInsulin, 'o','MarkerSize',5,'linewidth', 1.5,'Color',colorInhib, 'MarkerFaceColor','None')
     else
         disp('Something went wrong.. Incorrect inhibition type!')
     end
-    errorbar(20,value,upper-lower ,'o','linewidth',3,'Color',colorInhib, 'CapSize',12, 'MarkerFaceColor','auto')
+    hold on
+    errorbar(20,value,(upper-lower)/2 ,'o','linewidth',3,'Color',colorInhib, 'CapSize',12, 'MarkerFaceColor','auto')
 end
 
+plot(time(2:end), 2.^[data.TC_Exp1; data.TC_Exp2; data.TC_Exp3], 'o','MarkerSize',5,'linewidth', 1.5,'Color',colorNorm, 'MarkerFaceColor','None')
 errorbar(time,data.meanValues,data.SEMValues,'o','linewidth',3,'Color',colorNorm,'CapSize',12, 'MarkerFaceColor','auto') % Plot data
 
 axis tight
 box off
 xlabel('Time (min)')
 ylabel('Fold over basal')
 set(gca,'fontsize',26)
-set(gcf, 'Units','pixels', 'outerposition',[0 0 2560 1440], 'PaperType','a4')
+if formatFig9 % only for figure 9
+    set(gcf, 'Units','pixels', 'outerposition',[731   292   809   515],'PaperType','a4') %format for the figure 9 in the paper
+else
+    set(gcf, 'Units','pixels', 'outerposition',[0 0 2560 1440], 'PaperType','a4')
+end
 
 %% setup legend
 entries={'Normal'}';
@@ -253,9 +267,9 @@
 end
 if ~isempty(inhibSim)
     inhibEntries=cellstr(strcat(inhibType.type,num2str(inhibType.values')));
-    entries=[entries; inhibEntries; {[inhibType.type ' data']}];
+    entries=[entries; inhibEntries; {'';'';'';[inhibType.type ' data']}];
 end
-entries=[entries; {'Normal data'}];
+entries=[entries; {'';'';'';'Normal data'}];
 
 legend(entries,'location','best')
 title(titleStr, 'Interpreter','none')