-
Notifications
You must be signed in to change notification settings - Fork 0
/
TTest_FeaturesAmydis.m
190 lines (167 loc) · 7.41 KB
/
TTest_FeaturesAmydis.m
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
cellline = {'Optos','ExVivo','InVivo' };
imgroot = 'A:\Amydis\';
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,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)