bryan/hartman-server
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Squashed initial commit

Browse Source
This commit is contained in:
Bryan Roessler
2024-09-10 13:47:29 -04:00
commit 8ebb6ad265
6221 changed files with 2512206 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

393
qhtcp-workflow/apps/matlab/ezview/EZinterAgingDev0.m Executable file
View File

@@ -0,0 +1,393 @@
%single gene L based interaction shift display
function EZinterAgingDev0
global Exp
global matFile
[matFile,scansDir]=uigetfile('.mat','Open Experiment folder and data storage .mat file name','MultiSelect','on');
AgMPDM=load(fullfile(scansDir,'MasterPlateFiles','MPDMmat.mat'));
for i=1:size(matFile,2)
ExpOutmat{i}=fullfile(scansDir,matFile{i});
EScan{i}=load(ExpOutmat{1});
end
% single gene L based interaction shift display
% function EZinteractDev3
% expN=1;
% User Input decode for application
prompt={...
'Enter LeftSide Central Boundary in Percent:',...
'Enter RightSide Central Boundary in Percent:', ...
'Enter Perturbation Numbers for set intersect:' ...
'Remove No Growth Infinite Interactors:' ...
'Number of Bins for Histograms'...
'Subplots(Y), Multiple Plots(N), Suspend Plots(S)'};
% 'Select Experiment(zone) number:'
name='Interaction User Input';
numlines=1;
defaultanswer={'80','60','1','N','39','Y'};
answer=inputdlg(prompt,name,numlines,defaultanswer);
negPercent=str2double(cell2mat(answer(1)));
posPercent=str2double(cell2mat(answer(2)));
DMstr=cell2mat(answer(3));
DMcomas=strfind((cell2mat(answer(3))),',');
removInfinL=answer(4);
numBins=str2double(cell2mat(answer(5)));
subplotX=answer(6);
% expN=str2double(cell2mat(answer(7)));
n=0;
for i=DMcomas,
n=n+1
DMsel(n)=str2double(DMstr(i-1:i))
if i==max(DMcomas)
DMsel(n+1)=str2double(DMstr(i:end))
end
end
Rn=Exp(expN).RFmean;
Rs=Exp(expN).RFstd;
dmN=length(Exp(expN).DM.drug);
mpN=length(Exp(expN).MP);
% Intc1=3; IntcLst=5;
% Calculate Interaction values (with and without
% standardDeviation/Upper-Lower boundary compensation
for j=1:dmN
for m=1:mpN
scnN=j + (dmN*(m-1)) % 1,6,11..; 2,7,12 ..; 3,8,13..;
Xn{m,j,:}=Exp(expN).scan(scnN).plate(1).CFout(:,5); % Exp(expN).scan(DM{j}(m)).plate(1).CFout(:,5);
Xn{m,j,:}(Xn{m,j,:}==0)=140;
Xln{m,j,:}=Exp(expN).scan(scnN).plate(1).CFout(:,11); % Exp(expN).scan(DM{j}(m)).plate(1).CFout(:,11);
Xhn{m,j,:}=Exp(expN).scan(scnN).plate(1).CFout(:,12); % Exp(expN).scan(DM{j}(m)).plate(1).CFout(:,12);
intL{m,j,:}=(Xn{m,j,:} - Rn(j));
intL{m,j,:}(Xn{m,j,:}==140)=100;
intLhw{m,j,:}=((Xn{m,1,:}-Xn{m,j,:}) - Rn(1)-Rn(j));
intLhw{m,j,:}(Xn{m,j,:}==140)=100;
deltaXR{m,j}(Xn{m,j} >=(Rn(j)+Rs(j)))=( Xln{m,j}(Xn{m,j} >=(Rn(j)+Rs(j))))- (Rn(j)+Rs(j));
deltaXR{m,j}(Xn{m,j} < (Rn(j)-Rs(j)))=( Xhn{m,j}(Xn{m,j} < (Rn(j)-Rs(j))))- (Rn(j)-Rs(j));
Xneg=Xhn{m,j}- (Rn(j)-Rs(j));
Xpos=Xln{m,j}- (Rn(j)+Rs(j));
deltaXR{m,j}=zeros(1,384);
for i=1:length(Xpos(:))
% deltaXR{m,j}(i)=Xpos(i);
if deltaXR{m,j}(i)==0
try
if abs(Xpos(i))<abs(Xneg(i)), deltaXR{m,j}(i)=Xpos(i);end
catch
end
end
end
for i=1:length(Xneg(:))
if deltaXR{m,j}(i)==0, deltaXR{m,j}(i)=Xneg(i); end
try
if abs(Xpos(i))>abs(Xneg(i)), deltaXR{m,j}(i)=Xneg(i); end
catch
end
end
deltaXR{m,j,:}(Xln{m,j,:}==0)=100;
deltaXR{m,j,:}(isnan(Xln{m,j,:}))=120;
deltaXR{m,j,:}(Xhn{m,j,:}==0)=100;
deltaXR{m,j,:}(isnan(Xhn{m,j,:}))=120;
% Compile all gene related L values for the each pert-DM (j).
addend=(1+((m-1)*384)) % ((((m-1)*j)*384)+1);
intLcmp(addend:addend+383,j)=cell2mat(intL(m,j,:)); % ((addend:addend+383),j)=cell2mat(intL(j,m,:));
intLadjcmp(addend:addend+383,j)=cell2mat(deltaXR(m,j,:)); % ((addend:addend+383),j)=cell2mat(deltaXR(j,m,:));
end
% Remove RFs and Blank (or non annotated ' ') orf data Then
% Filter data per user intput
intLc{j}=intLcmp(:,j);
intLwoRFs{j}(1,:)=intLcmp(Exp(expN).mutSpotIndx.woRFs,j);
intLwoRFs{j}(2,:)=Exp(expN).mutSpotIndx.woRFs; % index of non-RF non-blank spots %Crude early intLcmp(385:(mpN-1)*384,j);
if strcmpi(removInfinL,'Y')
intLwoRFs0{j}(1,:)=intLwoRFs{j}(1,(intLwoRFs{j}(1,:)~=100)); % intLcmp(Exp(1).mutSpotIndx.woRFs,j);
intLwoRFs0{j}(2,:)=intLwoRFs{j}(2,(intLwoRFs{j}(1,:)~=100)); % intLcmp(385:(mpN-1)*384,j);
clear intLwoRFs
intLwoRFs{j}(1,:)=intLwoRFs0{j}(1,:);
intLwoRFs{j}(2,:)=intLwoRFs0{j}(2,:);
end
intLwoRFsorted{j}=sortrows(intLwoRFs{j}',1);
clear intLcmpSortGT0 intLcmpSortLT0
tempIntL=intLwoRFsorted{j}(:,1);
intLcmpSortGT0=tempIntL((tempIntL) >=0);
intLcmpSortLT0=tempIntL((tempIntL) <0);
centPosCnt=round(posPercent/100 * length(intLcmpSortGT0));
centNegCnt=round(negPercent/100 * length(intLcmpSortLT0));
intLposSel{j}=intLwoRFsorted{j}((length(intLcmpSortLT0)+centPosCnt): end,:);
intLnegSel{j}=intLwoRFsorted{j}((1:(length(intLcmpSortLT0)-centNegCnt)),:);
posIntboundryCentralVal(j)=intLcmpSortGT0((centPosCnt),:); % For Histogram use
negIntboundryCentralVal(j)=intLcmpSortLT0(((length(intLcmpSortLT0))-(centNegCnt)),:); % For Histogram use
% Find potential Interactors within selected range
if j==DMsel(1) % Intc1,
InterslstPos{1}=intLposSel{DMsel(1)}(:,2) % intLcmpposInd{Intc1}
InterslstNeg{1}=intLnegSel{DMsel(1)}(:,2) % intLcmpnegInd{Intc1}
elseif sum(ismember(DMsel,j))==1 %Intc1 && j<=IntcLst
InterslstPos{1}=(intersect(InterslstPos{1},intLposSel{j}(:,2))); % ,intLcmpposInd{j}))
InterslstNeg{1}=(intersect(InterslstNeg{1},intLnegSel{j}(:,2))); % ,intLcmpnegInd{j}))
end
% Convolute experiment spot index to get scan#, MP# and plateIndx needed
% later to obtain genename and other descriptors and correlate data
intLposDIndx{j}(:,2)=ceil((intLposSel{j}(:,2))/384); % mp plate numb column
intLposDIndx{j}(:,3)=(rem(intLposSel{j}(:,2),384));
nn=(intLposDIndx{j}(:,3)==0);
intLposDIndx{j}(nn,3)=384;
intLposDIndx{j}(:,1)=j + (dmN*((intLposDIndx{j}(:,2))-1)); % scan numb column %intLposDIndx(:,2)* intLposDIndx(:,3);
intLnegDIndx{j}(:,2)=ceil((intLnegSel{j}(:,2))/384); % mp plate numb column
intLnegDIndx{j}(:,3)=(rem(intLnegSel{j}(:,2),384));
nn=(intLposDIndx{j}(:,3)==0);
intLnegDIndx{j}(nn,3)=384;
intLnegDIndx{j}(:,1)=j + (dmN*((intLnegDIndx{j}(:,2))-1)); % scan numb
% ADJUSTED L for Reference Standard deviation(More conservative) Interaction List compilation
intLadjwoRFs{j}(1,:)=intLadjcmp(Exp(expN).mutSpotIndx.woRFs,j);
intLadjwoRFs{j}(2,:)=Exp(expN).mutSpotIndx.woRFs; % intLadjcmp(385:(mpN-1)*384,j); %intLadjcmp(Exp(expN).mutSpotIndx.woRFs,j);
if strcmpi(removInfinL,'Y')
intLadjwoRFs0{j}(1,:)=intLadjwoRFs{j}(1,(intLadjwoRFs{j}(1,:)~=100)) ; %intLcmp(Exp(1).mutSpotIndx.woRFs,j);
intLadjwoRFs0{j}(2,:)=intLadjwoRFs{j}(2,(intLadjwoRFs{j}(1,:)~=100)) ; % Remove Index where spots are infinite (=100);
clear intLadjwoRFs
intLadjwoRFs{j}(1,:)=intLadjwoRFs0{j}(1,:);
intLadjwoRFs{j}(2,:)=intLadjwoRFs0{j}(2,:);
end
intLwoRFsortedAdj{j}=sortrows(intLadjwoRFs{j}',1);
clear intLadjSortGT0 intLadjSortLT0
tempIntLadj=intLwoRFsortedAdj{j}(:,1);
intLadjSortGT0=tempIntLadj((tempIntLadj) >=0);
intLadjSortLT0=tempIntLadj((tempIntLadj) <0);
centPosCntAdj=round(posPercent/100 * length(intLadjSortGT0));
centNegCntAdj=round(negPercent/100 * length(intLadjSortLT0));
intLposSelAdj{j}=intLwoRFsortedAdj{j}((length(intLadjSortLT0)+centPosCntAdj): end,:);
intLnegSelAdj{j}=intLwoRFsortedAdj{j}((1:(length(intLadjSortLT0)-centNegCntAdj)),:);
posIntboundryCentralValAdj(j)=intLadjSortGT0((centPosCntAdj),:);
negIntboundryCentralValAdj(j)=intLadjSortLT0(((length(intLadjSortLT0))-(centNegCntAdj)),:);
if j==DMsel(1) % Intc1
InterslstPosAdj{1}=intLposSelAdj{DMsel(1)}(:,2) % intLcmpposInd{Intc1}
InterslstNegAdj{1}=intLnegSelAdj{DMsel(1)}(:,2) % intLcmpnegInd{Intc1}
elseif sum(ismember(DMsel,j))==1 % j>Intc1 && j<=IntcLst
InterslstPosAdj{1}=(intersect(InterslstPosAdj{1},intLposSelAdj{j}(:,2))); % ,intLcmpposInd{j}))
InterslstNegAdj{1}=(intersect(InterslstNegAdj{1},intLnegSelAdj{j}(:,2))); % ,intLcmpnegInd{j}))
end
% Convolute experiment spot index to get scan#, MP# and plateIndx needed
% later to obtain genename and other descriptors and correlate data
intLposDIndxAdj{j}(:,2)=ceil((intLposSelAdj{j}(:,2))/384); % mp plate numb column
intLposDIndxAdj{j}(:,3)=(rem(intLposSelAdj{j}(:,2),384));
nn=(intLposDIndxAdj{j}(:,3)==0);
intLposDIndx{j}(nn,3)=384;
intLposDIndxAdj{j}(:,1)=j + (dmN*((intLposDIndxAdj{j}(:,2))-1)); % scan numb column %intLposDIndx(:,2)* intLposDIndx(:,3);
intLnegDIndxAdj{j}(:,2)=ceil((intLnegSelAdj{j}(:,2))/384); % mp plate numb column
intLnegDIndxAdj{j}(:,3)=(rem(intLnegSelAdj{j}(:,2),384));
nn=(intLposDIndxAdj{j}(:,3)==0);
intLnegDIndxAdj{j}(nn,3)=384;
intLnegDIndxAdj{j}(:,1)=j + (dmN*((intLnegDIndxAdj{j}(:,2))-1)); % scan numb
end
% Get interaction values for each DM drugmedia agar type
IntersValsPos=intLcmp(InterslstPos{1},DMsel);
IntersValsNeg=intLcmp(InterslstNeg{1},DMsel);
IntersValsPosAdj=intLadjcmp(InterslstPosAdj{1},DMsel);
IntersValsNegAdj=intLadjcmp(InterslstNegAdj{1},DMsel);
% Build 'genelist' data sheet for interactors
selIntPx{1}(:,6)=InterslstPos{1};
selIntPx{1}(:,2)=ceil((InterslstPos{1})/384); % mp plate numb column
selIntPx{1}(:,3)=(rem(InterslstPos{1},384));
nn=(selIntPx{1}(:,3)==0);
selIntPx{1}(nn,3)=384;
selIntPx{1}(:,4)=ceil(selIntPx{1}(:,3)/24); % row numb
selIntPx{1}(:,5)=rem(selIntPx{1}(:,3),24);
mm=(selIntPx{1}(:,5)==0);
selIntPx{1}(mm,5)=24;
selIntPx{1}(:,1)=j + (dmN*((selIntPx{1}(:,2))-1)); % scan numb column %intLposDIndx(:,2)* intLposDIndx(:,3);
selIntP=cell2mat(selIntPx);
selIntNx{1}(:,6)=InterslstNeg{1};
selIntNx{1}(:,2)=ceil((InterslstNeg{1})/384); % mp plate numb column
selIntNx{1}(:,3)=(rem(InterslstNeg{1},384));
nn=(selIntNx{1}(:,3)==0);
selIntNx{1}(nn,3)=384;
selIntNx{1}(:,4)=ceil(selIntNx{1}(:,3)/24); % row numb
selIntNx{1}(:,5)=rem(selIntNx{1}(:,3),24);
mm=(selIntNx{1}(:,5)==0);
selIntNx{1}(mm,5)=24;
selIntNx{1}(:,1)=j + (dmN*((selIntNx{1}(:,2))-1)); % scan numb
selIntN=cell2mat(selIntNx);
for i=1:size(selIntP,1)
IPgene(i)=Exp(expN).MP(selIntP(i,2)).genename{1}(selIntP(i,3));
IPorf(i)=Exp(expN).MP(selIntP(i,2)).orf{1}(selIntP(i,3));
IPstrain(i)=Exp(expN).MP(selIntP(i,2)).strain{1}(selIntP(i,3));
IPspecifics(i)=Exp(expN).MP(selIntP(i,2)).specifics{1}(selIntP(i,3));
IPorfRep(i)=Exp(expN).MP(selIntP(i,2)).orfRep{1}(selIntP(i,3));
% Bad this is the L data for only the last selected DM perturbation
% Would need to calculate each scan# for each DMsel value
ipL(i)=Exp(expN).scan(selIntP(i,1)).plate(1).CFout(selIntP(i,3),5);
ipLlower(i)=Exp(expN).scan(selIntP(i,1)).plate(1).CFout(selIntP(i,3),11);
ipLupper(i)=Exp(expN).scan(selIntP(i,1)).plate(1).CFout(selIntP(i,3),12);
end
for i=1:size(selIntN,1)
INgene(i)=Exp(expN).MP(selIntN(i,2)).genename{1}(selIntN(i,3));
INorf(i)=Exp(expN).MP(selIntN(i,2)).orf{1}(selIntN(i,3));
INstrain(i)=Exp(expN).MP(selIntN(i,2)).strain{1}(selIntN(i,3));
INspecifics(i)=Exp(expN).MP(selIntN(i,2)).specifics{1}(selIntN(i,3));
INorfRep(i)=Exp(expN).MP(selIntN(i,2)).orfRep{1}(selIntN(i,3));
% Bad this is the L data for only the last selected DM perturbation
% Would need to calculate each scan# for each DMsel value
inL(i)=Exp(expN).scan(selIntN(i,1)).plate(1).CFout(selIntN(i,3),5);
inLlower(i)=Exp(expN).scan(selIntN(i,1)).plate(1).CFout(selIntN(i,3),11);
inLupper(i)=Exp(expN).scan(selIntN(i,1)).plate(1).CFout(selIntN(i,3),12);
end
% ADJUSTED with STD and curve fit boundaries to produce more conservative interaction values
% Build 'genelist' data sheet for interactors
selIntPxAdj{1}(:,2)=ceil((InterslstPosAdj{1})/384); %mp plate numb column
selIntPxAdj{1}(:,3)=(rem(InterslstPosAdj{1},384));
nn=(selIntPxAdj{1}(:,3)==0);
selIntPxAdj{1}(nn,3)=384;
selIntPxAdj{1}(:,4)=ceil(selIntPxAdj{1}(:,3)/24); %row numb
selIntPxAdj{1}(:,5)=rem(selIntPxAdj{1}(:,3),24);
mm=(selIntPxAdj{1}(:,5)==0);
selIntPxAdj{1}(mm,5)=24;
selIntPxAdj{1}(:,1)=j + (dmN*((selIntPxAdj{1}(:,2))-1)); %scan numb column %intLposDIndx(:,2)* intLposDIndx(:,3);
selIntPAdj=cell2mat(selIntPxAdj);
selIntNxAdj{1}(:,2)=ceil((InterslstNegAdj{1})/384); %mp plate numb column
selIntNxAdj{1}(:,3)=(rem(InterslstNegAdj{1},384));
nn=(selIntNxAdj{1}(:,3)==0);
selIntNxAdj{1}(nn,3)=384;
selIntNxAdj{1}(:,4)=ceil(selIntNxAdj{1}(:,3)/24); %row numb
selIntNxAdj{1}(:,5)=rem(selIntNxAdj{1}(:,3),24);
mm=(selIntNxAdj{1}(:,5)==0);
selIntNxAdj{1}(mm,5)=24;
selIntNxAdj{1}(:,1)=j + (dmN*((selIntNxAdj{1}(:,2))-1)); %scan numb
selIntNAdj=cell2mat(selIntNxAdj);
for i=1:size(selIntPAdj,1)
IPgeneAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).genename{1}(selIntPAdj(i,3));
IPorfAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).orf{1}(selIntPAdj(i,3));
IPstrainAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).strain{1}(selIntPAdj(i,3));
IPspecificsAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).specifics{1}(selIntPAdj(i,3));
IPorfRepAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).orfRep{1}(selIntPAdj(i,3));
% Bad this is the L data for only the last selected DM perturbation
% Would need to calculate each scan# for each DMsel value
ipLAdj(i)=Exp(expN).scan(selIntPAdj(i,1)).plate(1).CFout(selIntPAdj(i,3),5);
ipLlowerAdj(i)=Exp(expN).scan(selIntPAdj(i,1)).plate(1).CFout(selIntPAdj(i,3),11);
ipLupperAdj(i)=Exp(expN).scan(selIntPAdj(i,1)).plate(1).CFout(selIntPAdj(i,3),12);
end
for i=1:size(selIntNAdj,1)
INgeneAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).genename{1}(selIntNAdj(i,3));
INorfAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).orf{1}(selIntNAdj(i,3));
INstrainAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).strain{1}(selIntNAdj(i,3));
INspecificsAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).specifics{1}(selIntNAdj(i,3));
INorfRepAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).orfRep{1}(selIntNAdj(i,3));
%Bad this is the L data for only the last selected DM perturbation
%Would need to calculate each scan# for each DMsel value
inLAdj(i)=Exp(expN).scan(selIntNAdj(i,1)).plate(1).CFout(selIntNAdj(i,3),5);
inLlowerAdj(i)=Exp(expN).scan(selIntNAdj(i,1)).plate(1).CFout(selIntNAdj(i,3),11);
inLupperAdj(i)=Exp(expN).scan(selIntNAdj(i,1)).plate(1).CFout(selIntNAdj(i,3),12);
end
% Plot Histogram
% subplotX=1;
figure
if strcmpi(subplotX,'Y')
for j=1:dmN
histLdata=intLwoRFsorted{j}(:,1); % intLcmp(385:(mpN-1)*384,j);
% histLadjData=intLadjcmp(385:(mpN-1)*384,j);
hgLdat{j}=histfitJR(histLdata,numBins,'kernel');
x{j}=get(hgLdat{j}(2),'xdata');
y{j}=get(hgLdat{j}(2),'ydata');
xb{j}=get(hgLdat{j}(1),'xdata');
yb{j}=get(hgLdat{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,:);
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