394 lines
18 KiB
Matlab
Executable File
394 lines
18 KiB
Matlab
Executable File
%single gene L based interaction shift display
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function EZinterAgingDev0
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global Exp
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global matFile
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[matFile,scansDir]=uigetfile('.mat','Open Experiment folder and data storage .mat file name','MultiSelect','on');
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AgMPDM=load(fullfile(scansDir,'MasterPlateFiles','MPDMmat.mat'));
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for i=1:size(matFile,2)
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ExpOutmat{i}=fullfile(scansDir,matFile{i});
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EScan{i}=load(ExpOutmat{1});
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end
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% single gene L based interaction shift display
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% function EZinteractDev3
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% expN=1;
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% User Input decode for application
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prompt={...
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'Enter LeftSide Central Boundary in Percent:',...
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'Enter RightSide Central Boundary in Percent:', ...
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'Enter Perturbation Numbers for set intersect:' ...
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'Remove No Growth Infinite Interactors:' ...
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'Number of Bins for Histograms'...
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'Subplots(Y), Multiple Plots(N), Suspend Plots(S)'};
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% 'Select Experiment(zone) number:'
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name='Interaction User Input';
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numlines=1;
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defaultanswer={'80','60','1','N','39','Y'};
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answer=inputdlg(prompt,name,numlines,defaultanswer);
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negPercent=str2double(cell2mat(answer(1)));
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posPercent=str2double(cell2mat(answer(2)));
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DMstr=cell2mat(answer(3));
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DMcomas=strfind((cell2mat(answer(3))),',');
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removInfinL=answer(4);
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numBins=str2double(cell2mat(answer(5)));
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subplotX=answer(6);
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% expN=str2double(cell2mat(answer(7)));
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n=0;
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for i=DMcomas,
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n=n+1
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DMsel(n)=str2double(DMstr(i-1:i))
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if i==max(DMcomas)
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DMsel(n+1)=str2double(DMstr(i:end))
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end
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end
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Rn=Exp(expN).RFmean;
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Rs=Exp(expN).RFstd;
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dmN=length(Exp(expN).DM.drug);
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mpN=length(Exp(expN).MP);
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% Intc1=3; IntcLst=5;
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% Calculate Interaction values (with and without
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% standardDeviation/Upper-Lower boundary compensation
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for j=1:dmN
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for m=1:mpN
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scnN=j + (dmN*(m-1)) % 1,6,11..; 2,7,12 ..; 3,8,13..;
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Xn{m,j,:}=Exp(expN).scan(scnN).plate(1).CFout(:,5); % Exp(expN).scan(DM{j}(m)).plate(1).CFout(:,5);
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Xn{m,j,:}(Xn{m,j,:}==0)=140;
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Xln{m,j,:}=Exp(expN).scan(scnN).plate(1).CFout(:,11); % Exp(expN).scan(DM{j}(m)).plate(1).CFout(:,11);
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Xhn{m,j,:}=Exp(expN).scan(scnN).plate(1).CFout(:,12); % Exp(expN).scan(DM{j}(m)).plate(1).CFout(:,12);
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intL{m,j,:}=(Xn{m,j,:} - Rn(j));
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intL{m,j,:}(Xn{m,j,:}==140)=100;
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intLhw{m,j,:}=((Xn{m,1,:}-Xn{m,j,:}) - Rn(1)-Rn(j));
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intLhw{m,j,:}(Xn{m,j,:}==140)=100;
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deltaXR{m,j}(Xn{m,j} >=(Rn(j)+Rs(j)))=( Xln{m,j}(Xn{m,j} >=(Rn(j)+Rs(j))))- (Rn(j)+Rs(j));
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deltaXR{m,j}(Xn{m,j} < (Rn(j)-Rs(j)))=( Xhn{m,j}(Xn{m,j} < (Rn(j)-Rs(j))))- (Rn(j)-Rs(j));
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Xneg=Xhn{m,j}- (Rn(j)-Rs(j));
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Xpos=Xln{m,j}- (Rn(j)+Rs(j));
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deltaXR{m,j}=zeros(1,384);
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for i=1:length(Xpos(:))
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% deltaXR{m,j}(i)=Xpos(i);
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if deltaXR{m,j}(i)==0
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try
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if abs(Xpos(i))<abs(Xneg(i)), deltaXR{m,j}(i)=Xpos(i);end
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catch
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end
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end
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end
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for i=1:length(Xneg(:))
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if deltaXR{m,j}(i)==0, deltaXR{m,j}(i)=Xneg(i); end
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try
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if abs(Xpos(i))>abs(Xneg(i)), deltaXR{m,j}(i)=Xneg(i); end
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catch
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end
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end
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deltaXR{m,j,:}(Xln{m,j,:}==0)=100;
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deltaXR{m,j,:}(isnan(Xln{m,j,:}))=120;
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deltaXR{m,j,:}(Xhn{m,j,:}==0)=100;
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deltaXR{m,j,:}(isnan(Xhn{m,j,:}))=120;
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% Compile all gene related L values for the each pert-DM (j).
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addend=(1+((m-1)*384)) % ((((m-1)*j)*384)+1);
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intLcmp(addend:addend+383,j)=cell2mat(intL(m,j,:)); % ((addend:addend+383),j)=cell2mat(intL(j,m,:));
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intLadjcmp(addend:addend+383,j)=cell2mat(deltaXR(m,j,:)); % ((addend:addend+383),j)=cell2mat(deltaXR(j,m,:));
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end
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% Remove RFs and Blank (or non annotated ' ') orf data Then
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% Filter data per user intput
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intLc{j}=intLcmp(:,j);
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intLwoRFs{j}(1,:)=intLcmp(Exp(expN).mutSpotIndx.woRFs,j);
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intLwoRFs{j}(2,:)=Exp(expN).mutSpotIndx.woRFs; % index of non-RF non-blank spots %Crude early intLcmp(385:(mpN-1)*384,j);
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if strcmpi(removInfinL,'Y')
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intLwoRFs0{j}(1,:)=intLwoRFs{j}(1,(intLwoRFs{j}(1,:)~=100)); % intLcmp(Exp(1).mutSpotIndx.woRFs,j);
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intLwoRFs0{j}(2,:)=intLwoRFs{j}(2,(intLwoRFs{j}(1,:)~=100)); % intLcmp(385:(mpN-1)*384,j);
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clear intLwoRFs
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intLwoRFs{j}(1,:)=intLwoRFs0{j}(1,:);
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intLwoRFs{j}(2,:)=intLwoRFs0{j}(2,:);
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end
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intLwoRFsorted{j}=sortrows(intLwoRFs{j}',1);
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clear intLcmpSortGT0 intLcmpSortLT0
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tempIntL=intLwoRFsorted{j}(:,1);
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intLcmpSortGT0=tempIntL((tempIntL) >=0);
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intLcmpSortLT0=tempIntL((tempIntL) <0);
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centPosCnt=round(posPercent/100 * length(intLcmpSortGT0));
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centNegCnt=round(negPercent/100 * length(intLcmpSortLT0));
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intLposSel{j}=intLwoRFsorted{j}((length(intLcmpSortLT0)+centPosCnt): end,:);
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intLnegSel{j}=intLwoRFsorted{j}((1:(length(intLcmpSortLT0)-centNegCnt)),:);
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posIntboundryCentralVal(j)=intLcmpSortGT0((centPosCnt),:); % For Histogram use
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negIntboundryCentralVal(j)=intLcmpSortLT0(((length(intLcmpSortLT0))-(centNegCnt)),:); % For Histogram use
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% Find potential Interactors within selected range
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if j==DMsel(1) % Intc1,
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InterslstPos{1}=intLposSel{DMsel(1)}(:,2) % intLcmpposInd{Intc1}
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InterslstNeg{1}=intLnegSel{DMsel(1)}(:,2) % intLcmpnegInd{Intc1}
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elseif sum(ismember(DMsel,j))==1 %Intc1 && j<=IntcLst
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InterslstPos{1}=(intersect(InterslstPos{1},intLposSel{j}(:,2))); % ,intLcmpposInd{j}))
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InterslstNeg{1}=(intersect(InterslstNeg{1},intLnegSel{j}(:,2))); % ,intLcmpnegInd{j}))
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end
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% Convolute experiment spot index to get scan#, MP# and plateIndx needed
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% later to obtain genename and other descriptors and correlate data
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intLposDIndx{j}(:,2)=ceil((intLposSel{j}(:,2))/384); % mp plate numb column
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intLposDIndx{j}(:,3)=(rem(intLposSel{j}(:,2),384));
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nn=(intLposDIndx{j}(:,3)==0);
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intLposDIndx{j}(nn,3)=384;
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intLposDIndx{j}(:,1)=j + (dmN*((intLposDIndx{j}(:,2))-1)); % scan numb column %intLposDIndx(:,2)* intLposDIndx(:,3);
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intLnegDIndx{j}(:,2)=ceil((intLnegSel{j}(:,2))/384); % mp plate numb column
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intLnegDIndx{j}(:,3)=(rem(intLnegSel{j}(:,2),384));
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nn=(intLposDIndx{j}(:,3)==0);
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intLnegDIndx{j}(nn,3)=384;
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intLnegDIndx{j}(:,1)=j + (dmN*((intLnegDIndx{j}(:,2))-1)); % scan numb
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% ADJUSTED L for Reference Standard deviation(More conservative) Interaction List compilation
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intLadjwoRFs{j}(1,:)=intLadjcmp(Exp(expN).mutSpotIndx.woRFs,j);
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intLadjwoRFs{j}(2,:)=Exp(expN).mutSpotIndx.woRFs; % intLadjcmp(385:(mpN-1)*384,j); %intLadjcmp(Exp(expN).mutSpotIndx.woRFs,j);
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if strcmpi(removInfinL,'Y')
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intLadjwoRFs0{j}(1,:)=intLadjwoRFs{j}(1,(intLadjwoRFs{j}(1,:)~=100)) ; %intLcmp(Exp(1).mutSpotIndx.woRFs,j);
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intLadjwoRFs0{j}(2,:)=intLadjwoRFs{j}(2,(intLadjwoRFs{j}(1,:)~=100)) ; % Remove Index where spots are infinite (=100);
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clear intLadjwoRFs
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intLadjwoRFs{j}(1,:)=intLadjwoRFs0{j}(1,:);
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intLadjwoRFs{j}(2,:)=intLadjwoRFs0{j}(2,:);
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end
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intLwoRFsortedAdj{j}=sortrows(intLadjwoRFs{j}',1);
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clear intLadjSortGT0 intLadjSortLT0
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tempIntLadj=intLwoRFsortedAdj{j}(:,1);
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intLadjSortGT0=tempIntLadj((tempIntLadj) >=0);
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intLadjSortLT0=tempIntLadj((tempIntLadj) <0);
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centPosCntAdj=round(posPercent/100 * length(intLadjSortGT0));
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centNegCntAdj=round(negPercent/100 * length(intLadjSortLT0));
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intLposSelAdj{j}=intLwoRFsortedAdj{j}((length(intLadjSortLT0)+centPosCntAdj): end,:);
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intLnegSelAdj{j}=intLwoRFsortedAdj{j}((1:(length(intLadjSortLT0)-centNegCntAdj)),:);
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posIntboundryCentralValAdj(j)=intLadjSortGT0((centPosCntAdj),:);
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negIntboundryCentralValAdj(j)=intLadjSortLT0(((length(intLadjSortLT0))-(centNegCntAdj)),:);
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if j==DMsel(1) % Intc1
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InterslstPosAdj{1}=intLposSelAdj{DMsel(1)}(:,2) % intLcmpposInd{Intc1}
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InterslstNegAdj{1}=intLnegSelAdj{DMsel(1)}(:,2) % intLcmpnegInd{Intc1}
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elseif sum(ismember(DMsel,j))==1 % j>Intc1 && j<=IntcLst
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InterslstPosAdj{1}=(intersect(InterslstPosAdj{1},intLposSelAdj{j}(:,2))); % ,intLcmpposInd{j}))
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InterslstNegAdj{1}=(intersect(InterslstNegAdj{1},intLnegSelAdj{j}(:,2))); % ,intLcmpnegInd{j}))
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end
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% Convolute experiment spot index to get scan#, MP# and plateIndx needed
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% later to obtain genename and other descriptors and correlate data
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intLposDIndxAdj{j}(:,2)=ceil((intLposSelAdj{j}(:,2))/384); % mp plate numb column
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intLposDIndxAdj{j}(:,3)=(rem(intLposSelAdj{j}(:,2),384));
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nn=(intLposDIndxAdj{j}(:,3)==0);
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intLposDIndx{j}(nn,3)=384;
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intLposDIndxAdj{j}(:,1)=j + (dmN*((intLposDIndxAdj{j}(:,2))-1)); % scan numb column %intLposDIndx(:,2)* intLposDIndx(:,3);
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intLnegDIndxAdj{j}(:,2)=ceil((intLnegSelAdj{j}(:,2))/384); % mp plate numb column
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intLnegDIndxAdj{j}(:,3)=(rem(intLnegSelAdj{j}(:,2),384));
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nn=(intLposDIndxAdj{j}(:,3)==0);
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intLnegDIndxAdj{j}(nn,3)=384;
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intLnegDIndxAdj{j}(:,1)=j + (dmN*((intLnegDIndxAdj{j}(:,2))-1)); % scan numb
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end
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% Get interaction values for each DM drugmedia agar type
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IntersValsPos=intLcmp(InterslstPos{1},DMsel);
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IntersValsNeg=intLcmp(InterslstNeg{1},DMsel);
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IntersValsPosAdj=intLadjcmp(InterslstPosAdj{1},DMsel);
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IntersValsNegAdj=intLadjcmp(InterslstNegAdj{1},DMsel);
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% Build 'genelist' data sheet for interactors
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selIntPx{1}(:,6)=InterslstPos{1};
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selIntPx{1}(:,2)=ceil((InterslstPos{1})/384); % mp plate numb column
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selIntPx{1}(:,3)=(rem(InterslstPos{1},384));
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nn=(selIntPx{1}(:,3)==0);
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selIntPx{1}(nn,3)=384;
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selIntPx{1}(:,4)=ceil(selIntPx{1}(:,3)/24); % row numb
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selIntPx{1}(:,5)=rem(selIntPx{1}(:,3),24);
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mm=(selIntPx{1}(:,5)==0);
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selIntPx{1}(mm,5)=24;
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selIntPx{1}(:,1)=j + (dmN*((selIntPx{1}(:,2))-1)); % scan numb column %intLposDIndx(:,2)* intLposDIndx(:,3);
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selIntP=cell2mat(selIntPx);
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selIntNx{1}(:,6)=InterslstNeg{1};
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selIntNx{1}(:,2)=ceil((InterslstNeg{1})/384); % mp plate numb column
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selIntNx{1}(:,3)=(rem(InterslstNeg{1},384));
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nn=(selIntNx{1}(:,3)==0);
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selIntNx{1}(nn,3)=384;
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selIntNx{1}(:,4)=ceil(selIntNx{1}(:,3)/24); % row numb
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selIntNx{1}(:,5)=rem(selIntNx{1}(:,3),24);
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mm=(selIntNx{1}(:,5)==0);
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selIntNx{1}(mm,5)=24;
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selIntNx{1}(:,1)=j + (dmN*((selIntNx{1}(:,2))-1)); % scan numb
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selIntN=cell2mat(selIntNx);
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for i=1:size(selIntP,1)
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IPgene(i)=Exp(expN).MP(selIntP(i,2)).genename{1}(selIntP(i,3));
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IPorf(i)=Exp(expN).MP(selIntP(i,2)).orf{1}(selIntP(i,3));
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IPstrain(i)=Exp(expN).MP(selIntP(i,2)).strain{1}(selIntP(i,3));
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IPspecifics(i)=Exp(expN).MP(selIntP(i,2)).specifics{1}(selIntP(i,3));
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IPorfRep(i)=Exp(expN).MP(selIntP(i,2)).orfRep{1}(selIntP(i,3));
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% Bad this is the L data for only the last selected DM perturbation
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% Would need to calculate each scan# for each DMsel value
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ipL(i)=Exp(expN).scan(selIntP(i,1)).plate(1).CFout(selIntP(i,3),5);
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ipLlower(i)=Exp(expN).scan(selIntP(i,1)).plate(1).CFout(selIntP(i,3),11);
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ipLupper(i)=Exp(expN).scan(selIntP(i,1)).plate(1).CFout(selIntP(i,3),12);
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end
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for i=1:size(selIntN,1)
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INgene(i)=Exp(expN).MP(selIntN(i,2)).genename{1}(selIntN(i,3));
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INorf(i)=Exp(expN).MP(selIntN(i,2)).orf{1}(selIntN(i,3));
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INstrain(i)=Exp(expN).MP(selIntN(i,2)).strain{1}(selIntN(i,3));
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INspecifics(i)=Exp(expN).MP(selIntN(i,2)).specifics{1}(selIntN(i,3));
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INorfRep(i)=Exp(expN).MP(selIntN(i,2)).orfRep{1}(selIntN(i,3));
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% Bad this is the L data for only the last selected DM perturbation
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% Would need to calculate each scan# for each DMsel value
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inL(i)=Exp(expN).scan(selIntN(i,1)).plate(1).CFout(selIntN(i,3),5);
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inLlower(i)=Exp(expN).scan(selIntN(i,1)).plate(1).CFout(selIntN(i,3),11);
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inLupper(i)=Exp(expN).scan(selIntN(i,1)).plate(1).CFout(selIntN(i,3),12);
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end
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% ADJUSTED with STD and curve fit boundaries to produce more conservative interaction values
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% Build 'genelist' data sheet for interactors
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selIntPxAdj{1}(:,2)=ceil((InterslstPosAdj{1})/384); %mp plate numb column
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selIntPxAdj{1}(:,3)=(rem(InterslstPosAdj{1},384));
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nn=(selIntPxAdj{1}(:,3)==0);
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selIntPxAdj{1}(nn,3)=384;
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selIntPxAdj{1}(:,4)=ceil(selIntPxAdj{1}(:,3)/24); %row numb
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selIntPxAdj{1}(:,5)=rem(selIntPxAdj{1}(:,3),24);
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mm=(selIntPxAdj{1}(:,5)==0);
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selIntPxAdj{1}(mm,5)=24;
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selIntPxAdj{1}(:,1)=j + (dmN*((selIntPxAdj{1}(:,2))-1)); %scan numb column %intLposDIndx(:,2)* intLposDIndx(:,3);
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selIntPAdj=cell2mat(selIntPxAdj);
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selIntNxAdj{1}(:,2)=ceil((InterslstNegAdj{1})/384); %mp plate numb column
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selIntNxAdj{1}(:,3)=(rem(InterslstNegAdj{1},384));
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nn=(selIntNxAdj{1}(:,3)==0);
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selIntNxAdj{1}(nn,3)=384;
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selIntNxAdj{1}(:,4)=ceil(selIntNxAdj{1}(:,3)/24); %row numb
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selIntNxAdj{1}(:,5)=rem(selIntNxAdj{1}(:,3),24);
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mm=(selIntNxAdj{1}(:,5)==0);
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selIntNxAdj{1}(mm,5)=24;
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selIntNxAdj{1}(:,1)=j + (dmN*((selIntNxAdj{1}(:,2))-1)); %scan numb
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selIntNAdj=cell2mat(selIntNxAdj);
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for i=1:size(selIntPAdj,1)
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IPgeneAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).genename{1}(selIntPAdj(i,3));
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IPorfAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).orf{1}(selIntPAdj(i,3));
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IPstrainAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).strain{1}(selIntPAdj(i,3));
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IPspecificsAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).specifics{1}(selIntPAdj(i,3));
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IPorfRepAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).orfRep{1}(selIntPAdj(i,3));
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% Bad this is the L data for only the last selected DM perturbation
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% Would need to calculate each scan# for each DMsel value
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ipLAdj(i)=Exp(expN).scan(selIntPAdj(i,1)).plate(1).CFout(selIntPAdj(i,3),5);
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ipLlowerAdj(i)=Exp(expN).scan(selIntPAdj(i,1)).plate(1).CFout(selIntPAdj(i,3),11);
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ipLupperAdj(i)=Exp(expN).scan(selIntPAdj(i,1)).plate(1).CFout(selIntPAdj(i,3),12);
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end
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for i=1:size(selIntNAdj,1)
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INgeneAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).genename{1}(selIntNAdj(i,3));
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INorfAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).orf{1}(selIntNAdj(i,3));
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INstrainAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).strain{1}(selIntNAdj(i,3));
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INspecificsAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).specifics{1}(selIntNAdj(i,3));
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INorfRepAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).orfRep{1}(selIntNAdj(i,3));
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%Bad this is the L data for only the last selected DM perturbation
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%Would need to calculate each scan# for each DMsel value
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inLAdj(i)=Exp(expN).scan(selIntNAdj(i,1)).plate(1).CFout(selIntNAdj(i,3),5);
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inLlowerAdj(i)=Exp(expN).scan(selIntNAdj(i,1)).plate(1).CFout(selIntNAdj(i,3),11);
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inLupperAdj(i)=Exp(expN).scan(selIntNAdj(i,1)).plate(1).CFout(selIntNAdj(i,3),12);
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end
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|
|
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% Plot Histogram
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% subplotX=1;
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figure
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|
if strcmpi(subplotX,'Y')
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|
for j=1:dmN
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histLdata=intLwoRFsorted{j}(:,1); % intLcmp(385:(mpN-1)*384,j);
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% histLadjData=intLadjcmp(385:(mpN-1)*384,j);
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hgLdat{j}=histfitJR(histLdata,numBins,'kernel');
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x{j}=get(hgLdat{j}(2),'xdata');
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y{j}=get(hgLdat{j}(2),'ydata');
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xb{j}=get(hgLdat{j}(1),'xdata');
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yb{j}=get(hgLdat{j}(1),'ydata');
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ybpostot{j}=sum(yb{j}(2,(xb{j}(1,:)>=0)));
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ybnegtot{j}=sum(yb{j}(2,(xb{j}(1,:) <0)));
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xbb(j,:)=xb{j}(2,:);
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ybb(j,:)=yb{j}(2,:);
|
|
clf
|
|
end
|
|
|
|
% Figure
|
|
for j=1:dmN
|
|
histLdata=intLwoRFsorted{j}(:,1); % intLcmp(385:(mpN-1)*384,j);
|
|
hgL{j}=subplot(2, 4, j), histfitJR(histLdata,numBins,'kernel') ; hold %hgL{j}=histfit(intLcmp(:,j),31,'kernel')
|
|
subplot(2, 4, j),plot(posIntboundryCentralVal(j), 1:3000,'--r')
|
|
subplot(2, 4, j),plot(negIntboundryCentralVal(j), 1:3000,'--g')
|
|
hold off
|
|
end
|
|
scnsize=get(0,'screensize')
|
|
pos1=[round(scnsize(3)/40), round(scnsize(4)/2 +(scnsize(3)/80)),...
|
|
round(scnsize(3) -round(scnsize(3)/80)),round(scnsize(4)/2 -round(scnsize(4)/80))]
|
|
set(gcf,'outerposition',pos1)
|
|
set(gcf,'Name', 'Interaction Values ');
|
|
|
|
figure
|
|
for j=1:dmN
|
|
histLadjData=intLwoRFsortedAdj{j}(:,1); %intLadjcmp(385:(mpN-1)*384,j);
|
|
hgLadj{j}=subplot(2, 4, j),histfitJR(histLadjData,numBins,'kernel') ; hold %hgLadj{j}=histfit(intLadjcmp(:,j),31,'kernel')
|
|
subplot(2, 4, j),plot(posIntboundryCentralValAdj(j), 1:3000,'--r')
|
|
subplot(2, 4, j),plot(negIntboundryCentralValAdj(j), 1:3000,'--g')
|
|
hold off
|
|
end
|
|
pos2=[round(scnsize(3)/40), round(scnsize(4)/30),...
|
|
round(scnsize(3) -scnsize(3)/80),round(scnsize(4)/2 -scnsize(4)/80)]
|
|
set(gcf,'outerposition',pos2)
|
|
set(gcf,'Name', 'Interaction Compensated by Standard Deviation and Upper/Lower Curvefit boundaries')
|
|
elseif strcmpi(subplotX,'N')
|
|
for j=1:dmN
|
|
histLdata=intLwoRFsorted{j}(:,1); %intLcmp(385:(mpN-1)*384,j);
|
|
histLadjData=intLwoRFsortedAdj{j}(:,1); %intLadjcmp(385:(mpN-1)*384,j);%intLadjcmp(385:(mpN-1)*384,j); %intLcmp(:,j); %intLadjcmp(:,j);
|
|
figure
|
|
hgL{j}=histfitJR(histLdata,numBins,'kernel') ; hold %hgL{j}=histfit(intLcmp(:,j),31,'kernel')
|
|
plot(posIntboundryCentralVal(j), 1:3000,'--r')
|
|
plot(negIntboundryCentralVal(j), 1:3000,'--g')
|
|
hold off
|
|
figure
|
|
hgLadj{j}=histfitJR(histLadjData,numBins,'kernel') ; hold %hgLadj{j}=histfit(intLadjcmp(:,j),31,'kernel')
|
|
plot(posIntboundryCentralValAdj(j), 1:3000,'--r')
|
|
plot(negIntboundryCentralValAdj(j), 1:3000,'--g')
|
|
hold off
|
|
x{j}=get(hgL{j}(2),'xdata')
|
|
y{j}=get(hgL{j}(2),'ydata');
|
|
xb{j}=get(hgL{j}(1),'xdata')
|
|
yb{j}=get(hgL{j}(1),'ydata')
|
|
ybpostot{j}=sum(yb{j}(2,(xb{j}(1,:)>=0)))
|
|
ybnegtot{j}=sum(yb{j}(2,(xb{j}(1,:) <0)))
|
|
xbb(j,:)=xb{j}(2,:);
|
|
ybb(j,:)=yb{j}(2,:);
|
|
end
|
|
if strcmpi(subplotX,'N')
|
|
figure
|
|
bar3(ybb);
|
|
% xxbb=yb{1}(2,:);
|
|
% figure
|
|
end
|
|
else
|
|
end
|
|
% histograms placed in subplot figure else multiple histogram plots
|
|
|
|
if strcmpi(subplotX,'Y')
|
|
figure
|
|
bar3(ybb);
|
|
set(gcf,'Name', 'Unfiltered Interaction Histogram for all DrugMedias; NoGrowth Interactors set to 100hr (highest bin)')
|
|
%xxbb=yb{1}(2,:);
|
|
%figure
|
|
end
|
|
|
|
EZintPrint
|
|
a=1 % TODO what is this for
|
|
end
|