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Clustering2D__spICPTOFMS_SS.m

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+%HEADER%
+
+%***********************************%
+%Section Below does the 1D Clustering.
+%User parameters for cutoff of clusters (1D and 2D) and occurance frequency
+%for inclusion of elements in representative mmNP signature of each cluster
+CutoffVal=0.6;
+CutoffVal_2=0.3;
+OccurenceFreq=0.2;
+MinPartInClstr=5;
+
+%FileInformation
+ClusterMetaDataFile = 'ClusterInfoFile.xlsx';
+Filenames=readmatrix(ClusterMetaDataFile,'Sheet','Filename','Range',2,'OutputType','string');
+Filenames=Filenames(:,1);
+ElementNames=readmatrix(ClusterMetaDataFile,'Sheet','Elements','OutputType','string');
+q_Plasma=readmatrix(ClusterMetaDataFile,'Sheet','q_plasma','OutputType','double');
+PNCCorrFactors_mL=q_Plasma(:,1).*q_Plasma(:,2);
+PNCCorrFactors_mL=PNCCorrFactors_mL/1000;
+NbrElements=size(ElementNames,1);
+
+%Section Below does the 1D Clustering.
+ElementNames=reshape(ElementNames,1,NbrElements);
+
+ClstrProxyMassesCompile=[];
+ClstrProxyNamesCompile=[];
+ClstrNbrParticlesCompile=[];
+ClstrPNCsCompile=[];
+ClstrParticles3DCompile={};
+for b=1:size(Filenames,1)
+
+    NPData=xlsread(append(Filenames(b),'.csv'));
+
+    Z = linkage(NPData,'average','correlation');
+    ClstrAssign=cluster(Z,'Cutoff',CutoffVal,'criterion','distance');
+    NbrClusters=max(ClstrAssign);
+    figure();
+    h=dendrogram(Z,'ColorThreshold',CutoffVal);
+    TitleDendrogram = append(Filenames(b),'-Dendrogram');
+    title(TitleDendrogram);
+    saveas(gcf,TitleDendrogram);
+    close(gcf);
+
+    ClstrProxyMasses = [];
+    ClstrProxyNames =[];
+    ClstrDataNames =[];
+    ClstrNbrParticles = [];
+    ClstrParticles3D={};
+
+    for i=1:NbrClusters
+        index=find(ClstrAssign==i);
+        df=NPData(index,:);
+        SizeClstr=size(df);
+        if SizeClstr(1)>MinPartInClstr
+            NbrEventsInCluster=sum(df>0);
+            SumMassesInCluster=sum(df);
+            df(df==0)=NaN;
+            OneClassProxyMeanMass=nanmean(df);
+            df(isnan(df))=0;
+            ClusterOccurance=(NbrEventsInCluster/SizeClstr(1));
+            MaskOccurance=ClusterOccurance;
+            MaskOccurance(ClusterOccurance<OccurenceFreq)=0;
+            MaskOccurance(MaskOccurance>OccurenceFreq)=1;
+
+                for j=1:size(MaskOccurance)
+                    k=find(MaskOccurance==1);
+                end
+
+                for n=1:size(k,2)
+                    ClusterElements=ElementNames(1,k);
+                    ElementMasses_Cluster=df(:,k);
+                    Nbr_Cluster=NbrEventsInCluster(1,k);
+                end
+
+            [temp, order] = sort(Nbr_Cluster(1,:),'descend');
+            ClusterElementsSort = ClusterElements(:,order);
+
+            if size(ClusterElements,2)>2
+                OneClassProxyName = append(Filenames(b),'-',ClusterElementsSort(1),ClusterElementsSort(2),ClusterElementsSort(3));
+                OneClassDataName = append(Filenames(b),'_',ClusterElementsSort(1),ClusterElementsSort(2),ClusterElementsSort(3),'_Data');
+            elseif size(ClusterElements,2)>1
+                OneClassProxyName = append(Filenames(b),'-',ClusterElementsSort(1),ClusterElementsSort(2));
+                OneClassDataName = append(Filenames(b),'_',ClusterElementsSort(1),ClusterElementsSort(2),'_Data');
+            else
+                OneClassProxyName = append(Filenames(b),'-',ClusterElementsSort(1));
+                OneClassDataName = append(Filenames(b),'_',ClusterElementsSort(1),'_Data');
+            end
+
+
+           OneClassProxyMeanMass=OneClassProxyMeanMass.*MaskOccurance;
+           OneClassProxyMeanMass(isnan(OneClassProxyMeanMass))=0;
+
+
+           OneClassNbrParticles = SizeClstr(1);
+           OneClassNbrParticles(isnan(OneClassNbrParticles))=0;
+
+            currentFile = sprintf(OneClassDataName,'.mat');
+            save(currentFile,'df');
+
+        ClstrProxyMasses = cat(1,ClstrProxyMasses, OneClassProxyMeanMass);
+        ClstrProxyNames = cat(1,ClstrProxyNames,OneClassProxyName);
+        ClstrDataNames = cat(1,ClstrDataNames,OneClassDataName);
+        ClstrNbrParticles = cat(1,ClstrNbrParticles,OneClassNbrParticles);
+        ClstrParticles3D = cat(3,ClstrParticles3D,{df});
+
+        end
+    end
+
+ClstrPNCs = ClstrNbrParticles/PNCCorrFactors_mL(b);
+
+ClstrProxyMassesCompile=cat(1,ClstrProxyMassesCompile,ClstrProxyMasses);
+ClstrProxyNamesCompile=cat(1,ClstrProxyNamesCompile,ClstrProxyNames);  
+ClstrNbrParticlesCompile=cat(1,ClstrNbrParticlesCompile,ClstrNbrParticles);
+ClstrPNCsCompile=cat(1,ClstrPNCsCompile,ClstrPNCs);
+ClstrParticles3DCompile=cat(3,ClstrParticles3DCompile,ClstrParticles3D);
+end
+
+clear ClstrProxyMasses ClstrProxyNames ClstrDataNames ClstrNbrParticles ClstrParticles3D 
+clear OneClassProxyMass ClstrPNCs currentFile OneClassProxyName OneClassDataName NbrClusters 
+clear ClusterAssign TitleDendrogram NPData NbrEventsInCluster MaskOccurance SumMassesInCluster
+clear ElementMasses_Cluster OccurenceFreq OneClassNbrParticles NbrCluster
+clear ClusterElements ClusterElementsSort ClustOccurance SizeClstr df  
+
+%Section Below does the 2D Clustering.
+Z = linkage(ClstrProxyMassesCompile,'average','correlation');
+D = pdist(ClstrProxyMassesCompile);
+LeafOrder = optimalleaforder(Z,D);
+ClstrAssign=cluster(Z,'Cutoff',CutoffVal_2,'criterion','distance');
+
+NbrClusters=max(ClstrAssign);
+NbrProxyParticles=size(ClstrProxyMassesCompile);
+NbrProxyParticles=NbrProxyParticles(1);
+
+ClstrAssignSorted=ClstrAssign(LeafOrder,:);
+ClstrProxyMassesSorted = ClstrProxyMassesCompile(LeafOrder,:);
+ClstrNbrParticlesSorted=ClstrNbrParticlesCompile(LeafOrder,:);
+ClstrProxyNamesSorted=ClstrProxyNamesCompile(LeafOrder,:);
+ClstrPNCsSorted=ClstrPNCsCompile(LeafOrder,:);
+ClstrParticles3DSorted = ClstrParticles3DCompile(:,:,LeafOrder);
+
+ParticlesInClusters={};
+for k = 1:NbrClusters
+    index=find(ClstrAssignSorted==k);
+    OneClassParticles=[];
+    for i=1:size(index)
+        ParticleElementMasses=cell2mat(ClstrParticles3DSorted(:,:,index(i)));
+        OneClassParticles=vertcat(OneClassParticles,ParticleElementMasses);
+    end
+   ParticlesInClusters=cat(3,ParticlesInClusters,OneClassParticles);
+end
+PlotClstrOrder=unique(ClstrAssignSorted,'stable');
+ParticlesInClusters=ParticlesInClusters(:,:,PlotClstrOrder);
+
+for n=1:NbrClusters
+    Data=cell2mat(ParticlesInClusters(:,:,n));
+    DataName=strcat('2DClstr_',num2str(n));
+    currentFile = sprintf(DataName,'.mat');
+    save(currentFile,'Data');
+end
+
+clear ParticleElementMasses OneClassParticles OneClassProxyMeanMass
+
+
+%Section Below is plotting
+mycolormap=[1 1 1
+    0.817661881446838 0.803669035434723 0.959092855453491
+    0.635323822498322 0.607338070869446 0.918185710906982
+    0.45298570394516 0.411007136106491 0.877278566360474
+    0.270647615194321 0.214676186442375 0.836371421813965
+    0.275114297866821 0.234238088130951 0.870985686779022
+    0.278299987316132 0.255871415138245 0.899071455001831
+    0.27572038769722 0.278222441673279 0.91279798746109
+    0.27314081788063 0.300573468208313 0.926524519920349
+    0.270561218261719 0.322924494743347 0.940251052379608
+    0.267981618642807 0.345275491476059 0.953977525234222
+    0.265402019023895 0.367626518011093 0.967704057693481
+    0.262822449207306 0.389977544546127 0.98143059015274
+    0.260242849588394 0.412328571081161 0.995157122612
+    0.244033336639404 0.435833334922791 0.998833358287811
+    0.220642849802971 0.460257142782211 0.997285723686218
+    0.196333333849907 0.484719038009644 0.989152371883392
+    0.183404758572578 0.507371425628662 0.979795217514038
+    0.179921418428421 0.528638124465942 0.965907096862793
+    0.176438093185425 0.549904763698578 0.952019035816193
+    0.168742850422859 0.570261895656586 0.935871422290802
+    0.153999999165535 0.590200006961823 0.921800017356873
+    0.146011903882027 0.608914256095886 0.909545242786407
+    0.138023808598518 0.627628564834595 0.897290468215942
+    0.123752377927303 0.645028591156006 0.884787321090698
+    0.109480954706669 0.662428557872772 0.872284114360809
+    0.0952095240354538 0.679828584194183 0.859780967235565
+    0.0688714310526848 0.694771409034729 0.839357137680054
+    0.0296666659414768 0.708166658878326 0.81633335351944
+    0.00357142859138548 0.72026664018631 0.791700005531311
+    0.00665714265778661 0.731214284896851 0.766014277935028
+    0.0433285720646381 0.741095244884491 0.739409506320953
+    0.0963952392339706 0.75 0.712038099765778
+    0.140771433711052 0.758400022983551 0.684157133102417
+    0.171700000762939 0.766961932182312 0.655442833900452
+    0.193892866373062 0.775630950927734 0.623871445655823
+    0.216085717082024 0.784300029277802 0.592299997806549
+    0.246957138180733 0.791795253753662 0.55674284696579
+    0.290614277124405 0.797290503978729 0.518828570842743
+    0.345095902681351 0.794716358184814 0.476524502038956
+    0.399577528238297 0.7921422123909 0.434220403432846
+    0.454059153795242 0.789568066596985 0.391916334629059
+    0.50854080915451 0.786993861198425 0.349612236022949
+    0.563022434711456 0.78441971540451 0.307308167219162
+    0.617504060268402 0.781845569610596 0.265004068613052
+    0.671985685825348 0.779271423816681 0.222699999809265
+    0.724200010299683 0.769842863082886 0.191028565168381
+    0.773833334445953 0.759804785251617 0.164609521627426
+    0.820314288139343 0.74981427192688 0.153528571128845
+    0.863433361053467 0.740599989891052 0.159633338451385
+    0.903542876243591 0.733028590679169 0.177414283156395
+    0.939257144927979 0.728785693645477 0.209957137703896
+    0.972757160663605 0.729771435260773 0.239442855119705
+    0.995647609233856 0.743371427059174 0.237147614359856
+    0.989874601364136 0.767646014690399 0.223235711455345
+    0.984101593494415 0.79192066192627 0.209323808550835
+    0.978328585624695 0.816195249557495 0.195411905646324
+    0.97255551815033 0.840469837188721 0.181500002741814
+    0.966782510280609 0.864744484424591 0.167588099837303
+    0.961009502410889 0.889019072055817 0.153676196932793
+    0.963711082935333 0.912888884544373 0.137904763221741
+    0.966412723064423 0.936758756637573 0.122133336961269
+    0.969114303588867 0.960628569126129 0.106361903250217
+    0.976899981498718 0.983900010585785 0.0804999992251396
+    ];
+
+figure();
+h=dendrogram(Z,0,'Reorder',LeafOrder,'Labels',ClstrProxyNamesCompile,'orientation', 'left','ColorThreshold',CutoffVal_2);
+saveas(gcf,'2D-Clustering');
+close(gcf);
+
+
+figure();
+imagesc(flip(ClstrProxyMassesSorted));
+colorbar
+m=colorbar;
+set(m,'fontsize',10);
+m.Label.String = 'Attograms';
+set(m,'LineWidth', 1);
+set(m,'TickLength',0.02);
+set(m,'Location','eastoutside');
+XTickArray=1:NbrElements;
+YTickArray=1:size(ClstrProxyNamesSorted);
+set(gca,'colorscale','log')
+set(gca,'XTick',XTickArray);
+set(gca,'YTick',YTickArray);
+xticklabels(ElementNames)
+yticklabels(flip(ClstrProxyNamesSorted))
+saveas(gcf,'ProxyMassHeatmap');
+close(gcf);
+
+
+XTickArray=1:NbrElements;
+NbrProxies=size(ClstrProxyNamesSorted);
+NbrProxies=NbrProxies(1);
+YTickArray=1:size(ClstrProxyNamesSorted);
+
+figure();
+b=barh(ClstrNbrParticlesSorted);
+b.FaceColor = [0.9290 0.6940 0.1250];
+set(gca,'YTick',YTickArray);
+yticklabels(ClstrProxyNamesSorted);
+saveas(gcf,'ClstrNbrParticles');
+close(gcf);
+
+
+MaxCorr=max(Z);
+MaxCorr=MaxCorr(3);
+XMax=MaxCorr+0.1;
+YMax=NbrProxies+0.5;
+
+figure();
+subplot(1,20,[1,2])
+h=dendrogram(Z,0,'Reorder',LeafOrder,'orientation', 'left','ColorThreshold',CutoffVal_2);
+ClstrAssign=cluster(Z,'Cutoff',CutoffVal_2,'criterion','distance');
+set(gca,'YTick',YTickArray);
+set(gca,'fontsize',10)
+set(gca,'LineWidth',1.5)
+set(h,'LineWidth',1.5);
+axis([0 XMax 0.5 YMax]);
+yticklabels([]);
+axis off
+
+
+subplot(1,20,[5,16],'align')
+imagesc(flip(ClstrProxyMassesSorted));
+CBTicksMin=10;
+CBTicksMax=10^max((ceil(log10(max(ClstrProxyMassesSorted)))));
+CBTickArray=10.^(linspace(log10(CBTicksMin),log10(CBTicksMax),log10(CBTicksMax)-log10(CBTicksMin)+1));
+colorbar
+m=colorbar;
+set(m,'fontsize',10);
+m.Label.String = 'Attograms';
+set(m,'LineWidth', 0.5);
+set(m,'TickLength',0.02);
+set(m,'Ticks',CBTickArray);
+set(m,'Location','eastoutside');
+set(gca,'colorscale','log')
+caxis([CBTicksMin CBTicksMax]);
+colormap(mycolormap);
+set(gca,'XTick',XTickArray);
+set(gca,'YTick',YTickArray);
+set(gca,'fontsize',10)
+xticklabels(ElementNames)
+yticklabels(flip(ClstrProxyNamesSorted))
+
+
+XMin=10^(floor(log10(min(ClstrPNCsSorted))));
+XMax=10^(ceil(log10(max(ClstrPNCsSorted))));
+XTickArray=10.^(linspace(log10(XMin),log10(XMax),log10(XMax)-log10(XMin)+1));
+subplot(1,20,[18,20], 'align')
+b=barh(ClstrPNCsSorted);
+b.FaceColor = [0.9290 0.6940 0.1250];
+set(gca,'YTick',YTickArray);
+axis([XMin XMax 0.5 YMax]);
+set(gca,'YTick',[]);
+set(gca,'XTick',XTickArray);
+set(gca,'xscale','log')
+set(gca,'fontsize',10)
+set(gca,'LineWidth',1)
+ax=gca;
+ax.XLabel.String = 'Particles/mL';
+set(gca,'fontsize',10)
+saveas(gcf,'Cluster-Heatmap');
+
+clear ClstrProxyMassesCompile ClstrProxyNamesCompile ClstrNbrParticlesCompile
+clear ClstrPNCsCompile ClstrParticles3DCompile Data
+clear PlotClstrOrder NbrProxies MaxCorr
+clear ClstrAssign currentFile index
+clear i j k h n
+clear temp Z order D DataName
+clear XMax XMin XTickArray YMax YTickArray
+clear CBTickArray CBTicksMax CBTicksMin
+clear ax b m
+
+
+