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Copy pathTTest_Features.m
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TTest_Features.m
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cellline = {'TMK1','MKN7','SNU1','AZ521','MKN45', 'SCH','HS746T' };
imgroot = 'C:\ForAlex\GC_IMAGES\';
bins = [256 128 64 32 16 8];
rates = [1];
method.id = 3;
method.resolution = 6.45/40;
method.celllevel=1;
method.thresmethod = 'lowcommon';
for i=1:length(cellline)
dirs = dir([imgroot filesep cellline{i}]); dirs([1 2]) = [];
ALL_feats = [];
for j=1:length(dirs)
method.procfilesmatname = [pwd filesep 'meta' cellline{i} filesep dirs(j).name filesep 'procfiles.mat'];
method.resultdir = [pwd filesep 'meta' cellline{i} filesep dirs(j).name];
method.celllevel=1;
for b=1:1%length(bins)
for r=1:1%length(rates)
method.har_intbins = bins(b); method.downsamplerate = rates(r);
[this.feat, names, slfnames] = SC_Retrieve_Features(method);
ALL_feats = [ALL_feats; this.feat];
end
end
end
if i == 1
CTL_feats = ALL_feats(1:50,:);% number of images TMK1
TMK1c = ALL_feats(1:50,:);
DTX_feats = ALL_feats(53:102,:);
TMK1d = ALL_feats(53:102,:);
elseif i == 2
CTL_feats = ALL_feats(1:29,:);% number of images MKN7
MKN7c = ALL_feats(1:29,:);
DTX_feats = ALL_feats(31:59,:);
MKN7d = ALL_feats(31:59,:);
elseif i == 5
CTL_feats = ALL_feats(1:30,:);% number of images MKN45
MKN45c = ALL_feats(1:30,:);
DTX_feats = ALL_feats(31:60,:);
MKN45d = ALL_feats(31:60,:);
else
CTL_feats = ALL_feats(1:30,:);% number of images SNU1 or AZ521
DTX_feats = ALL_feats(31:60,:);
if i == 3
AZ521c = ALL_feats(1:30,:);
AZ521d = ALL_feats(31:60,:);
elseif i == 4
SNU1c = ALL_feats(1:30,:);
SNU1d = ALL_feats(31:60,:);
elseif i == 6
SCHc = ALL_feats(1:30,:);
SCHd = ALL_feats(31:60,:);
elseif i == 7
HS746Tc = ALL_feats(1:30,:);
HS746Td = ALL_feats(31:60,:);
end
end
% keyboard
% p2 = zeros(21,200);
% for j = 1 : 200
% % FIND IF ITS UP OR DOWN - 21 features - 21 values
% TMK1ch = sign(median(TMK1c,1) - median(TMK1d,1))
% MKN7ch = sign(median(MKN7c,1) - median(MKN7d,1))
% MKN45ch = sign(median(MKN45c,1) - median(MKN45d,1))
% AZ521ch = sign(median(AZ521c,1) - median(AZ521d,1))
% SNU1ch = sign(median(SNU1c,1) - median(SNU1d,1))
% SCHch = sign(median(SCHc,1) - median(SCHd,1))
% HS746Tch = sign(median(HS746Tc,1) - median(HS746Td,1))
[H, p] = ttest(CTL_feats, DTX_feats, 0.01);
% p = p*21% Correction by the number of features
% p2(:,j) = p1';
% end
% p = mean (p2,2);
figure, boxplot([CTL_feats(:,1)/1000,DTX_feats(:,1)/1000,CTL_feats(:,2)/10000000,DTX_feats(:,2)/10000000,CTL_feats(:,3)/10000,DTX_feats(:,3)/10000,...
CTL_feats(:,4)*10,DTX_feats(:,4)*10,...
CTL_feats(:,5)*5,DTX_feats(:,5)*5,CTL_feats(:,6),DTX_feats(:,6),...
CTL_feats(:,8)*10,DTX_feats(:,8)*10,...
CTL_feats(:,9)/100,DTX_feats(:,9)/100,...
CTL_feats(:,13)*100,DTX_feats(:,13)*100],'notch','on','whisker',1.5, ...
'widths', 0.8, 'labels', {'1','1D', '2','2D','3','3D','4','4D',...
'5','5D','6','6D','8','8D','9','9D','13','13D', },...
'positions' , [ 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35])
ylim([-1 15])
ylabel('13 Feat of MT Texture After 100nM DTX');
title(cellline{i})
figure, boxplot([CTL_feats(:,1)/1000,DTX_feats(:,1)/1000,CTL_feats(:,2)/10000000,DTX_feats(:,2)/10000000,CTL_feats(:,3)/10000,DTX_feats(:,3)/10000,...
CTL_feats(:,4)/1000,DTX_feats(:,4)/1000,...
CTL_feats(:,5)/1000,DTX_feats(:,5)/1000,CTL_feats(:,6),DTX_feats(:,6),...
CTL_feats(:,7)*5,DTX_feats(:,7)*5,CTL_feats(:,8)*10,DTX_feats(:,8)*10,...
CTL_feats(:,9)/100,DTX_feats(:,9)/100,...
CTL_feats(:,10),DTX_feats(:,10),...
CTL_feats(:,11)/20,DTX_feats(:,11)/20,...
CTL_feats(:,12),DTX_feats(:,12),...
CTL_feats(:,13),DTX_feats(:,13)],'notch','on','whisker',1.5, ...
'widths', 0.8, 'labels', {'1','1D', '2','2D','3','3D','4','4D',...
'5','5D','6','6D','7','7D','8','8D','9','9D','10','10D','11','11D','12','12D','13','13D', },...
'positions' , [ 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51])
% ylim([-1 3])
ylabel('13 Feat of MT Texture After 100nM DTX');
title(cellline{i})
figure, boxplot([CTL_feats(:,14)/1000,DTX_feats(:,14)/1000,CTL_feats(:,15)/10000000,DTX_feats(:,15)/10000000,CTL_feats(:,16)/10000,DTX_feats(:,16)/10000,...
CTL_feats(:,17)*10,DTX_feats(:,17)*10,...
CTL_feats(:,18)*5,DTX_feats(:,18)*5,CTL_feats(:,19),DTX_feats(:,19),...
CTL_feats(:,20)*5,DTX_feats(:,20)*5,CTL_feats(:,21)*10,DTX_feats(:,21)*10],'notch','on','whisker',1.5, ...
'widths', 0.8, 'labels', {'14','14D', '15','15D','16','16D','17','17D',...
'18','18D','19','19D','20','20D','21','21D'},...
'positions' , [ 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31])
% ylim([-1 15])
ylabel('8 (#14-21) Feat of MT Texture After 100nM DTX');
title(cellline{i})
fileName = [cellline{i} '_CTL_vs_DTX__FULL_SET_T-Test.txt'];
fid = fopen(fileName ,'w');
fprintf(fid, '%s\n', ['Cell Line:' cellline{i}]);
fprintf(fid, 'FeatureName\tp<0.01\tp\n');
for f_idx = 1:length(names)
fprintf(fid, '%s\t%d\t%.4f\n', names{f_idx}, H(f_idx), p(f_idx));
end
fclose(fid);
fprintf(1, [fileName ' is created.\n']);
end
% PLOT ONLY CONTROL/UNTREATED 30, 30, 29, 50, 30, 30, 31
aux(1:21)=nan;
data=zeros(21,6);
li = [2,3,4,5,6,7,9,10,11,12,13,14,15,19,20,21];
for i = 1:21
strg=sprintf('%%.%dd',2);
indxStr=sprintf(strg,i);
SC = [SCHc(:,i);aux(1:end-1)'];
H= [HS746Tc(:,i);aux(1:end-1)'];
M=[MKN7c(:,i);aux(1:end)'];
SN = [SNU1c(:,i);aux(1:end-1)'];
A = [AZ521c(:,i);aux(1:end-1)'];
M4 = [ MKN45c(:,i); aux(1:end-1)'];
mSc = mean(SCHc(:,i));
mH=mean(HS746Tc(:,i));
mM=mean(MKN7c(:,i));
mSN=mean(SNU1c(:,i));
mA=mean(AZ521c(:,i));
mT=mean(TMK1c(:,i));
dSc = mean(SCHd(:,i));
dH=mean(HS746Td(:,i));
dM=mean(MKN7d(:,i));
dSN=mean(SNU1d(:,i));
dA=mean(AZ521d(:,i));
dT=mean(TMK1d(:,i));
% data(i,:) = [(mSN-dSN)*100/dSN,(mT-dT)*100/dT,(mA-dA)*100/dA,(mM-dM)*100/dM,(mSc-dSc)*100/dSc,(mH-dH)*100/dH];
data(i,:) = [mSN/dSN,mT/dT,mA/dA,mM/dM,mSc/dSc,mH/dH];
% data(i,:) = [mSN-dSN,mT-dT,mA-dA,mM-dM,mSc-dSc,mH-dH];
% figure, boxplot([ SC, H, M ,TMK1c(:,i), SN , A ,M4],'notch','on','whisker',1.5, ...
% 'widths', 0.8, 'labels', {'SCH','HS746T','MKN7','TMK1','SNU1','AZ521','MKN45'},...
% 'positions' , [ 1, 3, 5, 7, 9, 11, 13 ])
% ylim([-1 15])
% ylabel('All 7 cell lines, untreated');
% title(['Feature number ',indxStr ])
clear SC,H,M,SN,A,M4;
SC = [SCHd(:,i);aux(1:end-1)'];
H= [HS746Td(:,i);aux(1:end-1)'];
M=[MKN7d(:,i);aux(1:end)'];
SN = [SNU1d(:,i);aux(1:end-1)'];
A = [AZ521d(:,i);aux(1:end-1)'];
M4 = [ MKN45d(:,i); aux(1:end-1)'];
% figure, boxplot([ SC, H, M ,TMK1d(:,i), SN , A ,M4],'notch','on','whisker',1.5, ...
% 'widths', 0.8, 'labels', {'SCH','HS746T','MKN7','TMK1','SNU1','AZ521','MKN45'},...
% 'positions' , [ 1, 3, 5, 7, 9, 11, 13 ])
% ylim([-1 15])
ylabel('All 7 cell lines, 100nM DTX');
title(['Feature number ',indxStr ])
end
li = [2,3,4,5,6,7,9,10,11,12,13,14,15,19,20,21];
HeatMap(data*1000)