-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathgroupedBarplots.m
executable file
·230 lines (197 loc) · 11.1 KB
/
groupedBarplots.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
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
clear all
close all
clc
% Load data
% load('/Volumes/WD Ezra/Data/Synaptosomes/Experiment_37C/Results/results_combined_after_overlap_threshold.mat');
% load('/Volumes/WD Ezra/Data/Synaptosomes/Experiment_37C/Results/Results_combined/ripley/clustersizes.mat');
% load('/Volumes/WD Ezra/Data/Synaptosomes/Experiment_37C/Results/Results_combined/ripley/interclusterdist.mat');
load('/Volumes/WD Ezra/Data/Synaptosomes/Experiment_4C/Results/results_combined_after_overlap_threshold.mat');
load('/Volumes/WD Ezra/Data/Synaptosomes/Experiment_4C/Results/Results_combined/ripley/clustersizes.mat');
load('/Volumes/WD Ezra/Data/Synaptosomes/Experiment_4C/Results/Results_combined/ripley/interclusterdist.mat');
output_dir = '/Users/Ezra/Desktop';
temperature = '4';
%% Creating output folder in output_dir
% Create new output folder
path_output = fullfile(output_dir,'grouped_barplots');
if exist(path_output, 'dir')
opts.Interpreter = 'tex';
opts.Default = 'Continue';
quest = '\fontsize{12}An output folder ''Grouped barplots'' already exists. If you continue, data in this folder might be overwritten.';
answer = questdlg(quest,'Message','Cancel','Continue',opts);
if strcmp(answer,'Continue')
mkdir(path_output);
else
return
end
else
mkdir(path_output);
end
%% Plot
T = results_combined_after_filtering;
% Get mean and sd of all the data to be included in grouped barplots
[area_mCling_mean, area_mCling_std] = ...
getMeanAndStdConditions(T.Area,T.condition,{'phys','egta','egtak'});
[overlapWithGreen_mean, overlapWithGreen_std] = ...
getMeanAndStdConditions(T.OverlapWithGreen,T.condition,{'phys','egta','egtak'});
[overlapWithBlue_mean, overlapWithBlue_std] = ...
getMeanAndStdConditions(T.OverlapWithBlue,T.condition,{'phys','egta','egtak'});
[weightedOverlapWithGreen_mean, weightedOverlapWithGreen_std] = ...
getMeanAndStdConditions(T.WeightedOverlapWithGreen,T.condition,{'phys','egta','egtak'});
[weightedOverlapWithBlue_mean, weightedOverlapWithBlue_std] = ...
getMeanAndStdConditions(T.WeightedOverlapWithBlue,T.condition,{'phys','egta','egtak'});
size_phys_RC_mean = mean(clustersize_phys_RC);
size_phys_GC_mean = mean(clustersize_phys_GC);
size_phys_BC_mean = mean(clustersize_phys_BC);
interclusterdist_phys_RG_mean = mean(interclusterdist_phys_RG);
interclusterdist_phys_RB_mean = mean(interclusterdist_phys_RB);
interclusterdist_phys_GB_mean = mean(interclusterdist_phys_GB);
size_phys_RC_std = std(clustersize_phys_RC);
size_phys_GC_std = std(clustersize_phys_GC);
size_phys_BC_std = std(clustersize_phys_BC);
interclusterdist_phys_RG_std = std(interclusterdist_phys_RG);
interclusterdist_phys_RB_std = std(interclusterdist_phys_RB);
interclusterdist_phys_GB_std = std(interclusterdist_phys_GB);
size_egta_RC_mean = mean(clustersize_egta_RC);
size_egta_GC_mean = mean(clustersize_egta_GC);
size_egta_BC_mean = mean(clustersize_egta_BC);
interclusterdist_egta_RG_mean = mean(interclusterdist_egta_RG);
interclusterdist_egta_RB_mean = mean(interclusterdist_egta_RB);
interclusterdist_egta_GB_mean = mean(interclusterdist_egta_GB);
size_egta_RC_std = std(clustersize_egta_RC);
size_egta_GC_std = std(clustersize_egta_GC);
size_egta_BC_std = std(clustersize_egta_BC);
interclusterdist_egta_RG_std = std(interclusterdist_egta_RG);
interclusterdist_egta_RB_std = std(interclusterdist_egta_RB);
interclusterdist_egta_GB_std = std(interclusterdist_egta_GB);
size_egtak_RC_mean = mean(clustersize_egtak_RC);
size_egtak_GC_mean = mean(clustersize_egtak_GC);
size_egtak_BC_mean = mean(clustersize_egtak_BC);
interclusterdist_egtak_RG_mean = mean(interclusterdist_egtak_RG);
interclusterdist_egtak_RB_mean = mean(interclusterdist_egtak_RB);
interclusterdist_egtak_GB_mean = mean(interclusterdist_egtak_GB);
size_egtak_RC_std = std(clustersize_egtak_RC);
size_egtak_GC_std = std(clustersize_egtak_GC);
size_egtak_BC_std = std(clustersize_egtak_BC);
interclusterdist_egtak_RG_std = std(interclusterdist_egtak_RG);
interclusterdist_egtak_RB_std = std(interclusterdist_egtak_RB);
interclusterdist_egtak_GB_std = std(interclusterdist_egtak_GB);
clustersize_RC_mean = [size_phys_RC_mean size_egta_RC_mean size_egtak_RC_mean];
clustersize_GC_mean = [size_phys_GC_mean size_egta_GC_mean size_egtak_GC_mean];
clustersize_BC_mean = [size_phys_BC_mean size_egta_BC_mean size_egtak_BC_mean];
interclusterdist_RG_mean = [interclusterdist_phys_RG_mean interclusterdist_egta_RG_mean interclusterdist_egtak_RG_mean];
interclusterdist_RB_mean = [interclusterdist_phys_RB_mean interclusterdist_egta_RB_mean interclusterdist_egtak_RB_mean];
interclusterdist_GB_mean = [interclusterdist_phys_GB_mean interclusterdist_egta_GB_mean interclusterdist_egtak_GB_mean];
clustersize_RC_std = [size_phys_RC_std size_egta_RC_std size_egtak_RC_std];
clustersize_GC_std = [size_phys_GC_std size_egta_GC_std size_egtak_GC_std];
clustersize_BC_std = [size_phys_BC_std size_egta_BC_std size_egtak_BC_std];
interclusterdist_RG_std = [interclusterdist_phys_RG_std interclusterdist_egta_RG_std interclusterdist_egtak_RG_std];
interclusterdist_RB_std = [interclusterdist_phys_RB_std interclusterdist_egta_RB_std interclusterdist_egtak_RB_std];
interclusterdist_GB_std = [interclusterdist_phys_GB_std interclusterdist_egta_GB_std interclusterdist_egtak_GB_std];
% Rescale the data to fit on a plot (too many differences in scales otherwise)
norm_area_mCling_mean = area_mCling_mean/area_mCling_mean(1);
norm_overlapWithGreen_mean = overlapWithGreen_mean/overlapWithGreen_mean(1);
norm_overlapWithBlue_mean = overlapWithBlue_mean/overlapWithBlue_mean(1);
norm_weightedOverlapWithGreen_mean = weightedOverlapWithGreen_mean/weightedOverlapWithGreen_mean(1);
norm_weightedOverlapWithBlue_mean = weightedOverlapWithBlue_mean/weightedOverlapWithBlue_mean(1);
norm_clustersize_RC_mean = clustersize_RC_mean/clustersize_RC_mean(1);
norm_clustersize_GC_mean = clustersize_GC_mean/clustersize_GC_mean(1);
norm_clustersize_BC_mean = clustersize_BC_mean/clustersize_BC_mean(1);
norm_interclusterdist_RG_mean = interclusterdist_RG_mean/interclusterdist_RG_mean(1);
norm_interclusterdist_RB_mean = interclusterdist_RB_mean/interclusterdist_RB_mean(1);
norm_interclusterdist_GB_mean = interclusterdist_GB_mean/interclusterdist_GB_mean(1);
norm_area_mCling_std = area_mCling_std/area_mCling_mean(1);
norm_overlapWithGreen_std = overlapWithGreen_std/overlapWithGreen_mean(1);
norm_overlapWithBlue_std = overlapWithBlue_std/overlapWithBlue_mean(1);
norm_weightedOverlapWithGreen_std = weightedOverlapWithGreen_std/weightedOverlapWithGreen_mean(1);
norm_weightedOverlapWithBlue_std = weightedOverlapWithBlue_std/weightedOverlapWithBlue_mean(1);
norm_clustersize_RC_std = clustersize_RC_std/clustersize_RC_mean(1);
norm_clustersize_GC_std = clustersize_GC_std/clustersize_GC_mean(1);
norm_clustersize_BC_std = clustersize_BC_std/clustersize_BC_mean(1);
norm_interclusterdist_RG_std = interclusterdist_RG_std/interclusterdist_RG_mean(1);
norm_interclusterdist_RB_std = interclusterdist_RB_std/interclusterdist_RB_mean(1);
norm_interclusterdist_GB_std = interclusterdist_GB_std/interclusterdist_GB_mean(1);
fig1 = figure;
clear var ctr ydt
data = [norm_area_mCling_mean' norm_overlapWithGreen_mean' ...
norm_overlapWithBlue_mean' norm_weightedOverlapWithGreen_mean' ...
norm_weightedOverlapWithBlue_mean'];
Std = [norm_area_mCling_std' norm_overlapWithGreen_std' ...
norm_overlapWithBlue_std' norm_weightedOverlapWithGreen_std' ...
norm_weightedOverlapWithBlue_std'];
hBar = bar(1:3,data);
for i = 1:size(data,2)
ctr(i,:) = bsxfun(@plus, hBar(1).XData, [hBar(i).XOffset]');
ydt(i,:) = hBar(i).YData;
end
hold on
errorbar(ctr, ydt, Std', '.k')
set(gca,'XTick',1:3,'XTickLabel',{'PHYS','EGTA','EGTA/K+'})
legend({'Area mCling','Overlap mCling/a-syn','Overlap mCling/VAMP2','Weighted overlap mCling/a-syn','Weighted overlap mCling/VAMP2'},'Location','northwest')
ylabel('Value normalized by value PHYS condition')
title(strcat('Influence of area on overlap (',temperature,' °C)'));
set(gca,'fontsize',14);
hold off
fig2 = figure;
clear var ctr ydt
data = [norm_area_mCling_mean' norm_clustersize_RC_mean' ...
norm_clustersize_GC_mean' norm_clustersize_BC_mean' ...
norm_overlapWithGreen_mean' norm_overlapWithBlue_mean' ...
norm_weightedOverlapWithGreen_mean' norm_weightedOverlapWithBlue_mean'];
Std = [norm_area_mCling_std' norm_clustersize_RC_std' ...
norm_clustersize_GC_std' norm_clustersize_BC_std' ...
norm_overlapWithGreen_std' norm_overlapWithBlue_std' ...
norm_weightedOverlapWithGreen_std' norm_weightedOverlapWithBlue_std'];
hBar = bar(1:3,data);
for i = 1:size(data,2)
ctr(i,:) = bsxfun(@plus, hBar(1).XData, [hBar(i).XOffset]');
ydt(i,:) = hBar(i).YData;
end
hold on
errorbar(ctr, ydt, Std', '.k')
set(gca,'XTick',1:3,'XTickLabel',{'PHYS','EGTA','EGTA/K+'})
legend({'Area mCling','Size mCling','Size a-synuclein','Size VAMP2','Overlap mCling/a-syn','Overlap mCling/VAMP2','Weighted overlap mCling/a-syn','Weighted overlap mCling/VAMP2'},'Location','northwest')
ylabel('Value normalized by value PHYS condition')
title(strcat('Influence of area on overlap (',temperature,' °C)'));
set(gca,'fontsize',14);
fig3 = figure;
clear var ctr ydt
data = [interclusterdist_RG_mean' interclusterdist_RB_mean' interclusterdist_GB_mean'];
Std = [interclusterdist_RG_std' interclusterdist_RB_std' interclusterdist_GB_std'];
hBar = bar(1:3,data);
for i = 1:size(data,2)
ctr(i,:) = bsxfun(@plus, hBar(1).XData, [hBar(i).XOffset]');
ydt(i,:) = hBar(i).YData;
end
hold on
errorbar(ctr, ydt, Std', '.k')
set(gca,'XTick',1:3,'XTickLabel',{'PHYS','EGTA','EGTA/K+'})
legend({'Intercluster distance mCling/a-syn','Intercluster distance mCling/VAMP2','Intercluster distance a-syn/VAMP2'},'Location','northwest')
ylabel('Value normalized by value PHYS condition')
title(strcat('Intercluster distance comparison (',temperature,' °C)'));
set(gca,'fontsize',14);
hold off
fig4 = figure;
clear var ctr ydt
data = [norm_weightedOverlapWithGreen_mean' norm_weightedOverlapWithBlue_mean'];
Std = [norm_weightedOverlapWithGreen_std' norm_weightedOverlapWithBlue_std'];
hBar = bar(1:3,data);
for i = 1:size(data,2)
ctr(i,:) = bsxfun(@plus, hBar(1).XData, [hBar(i).XOffset]');
ydt(i,:) = hBar(i).YData;
end
hold on
errorbar(ctr, ydt, Std', '.k')
set(gca,'XTick',1:3,'XTickLabel',{'PHYS','EGTA','EGTA/K+'})
legend({'Weighted overlap mCling/a-syn','Weighted overlap mCling/VAMP2'},'Location','northwest')
ylabel('Value normalized by value PHYS condition')
title(strcat('Weighted overlap comparison (',temperature,' °C)'));
set(gca,'fontsize',14);
hold off
path_fig1 = fullfile(path_output,strcat('groupedBarplot_overlap_',temperature,'C-1.fig'));
path_fig2 = fullfile(path_output,strcat('groupedBarplot_overlap_',temperature,'C-2.fig'));
path_fig3 = fullfile(path_output,strcat('groupedBarplot_interactiondist_',temperature,'C.fig'));
path_fig4 = fullfile(path_output,strcat('groupedBarplot_weighted_overlaps_',temperature,'C.fig'));
savefig(fig1,path_fig1)
savefig(fig2,path_fig2)
savefig(fig3,path_fig3)
savefig(fig4,path_fig4)