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Plot_DotComps2_hb.m
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Plot_DotComps2_hb.m
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%% Plot_DotComps2_hb.m %%
%
% Analyzing New Shadow data
%
%
% Alistair Boettiger Date Begun: 03/05/10
% Levine Lab Functional Since: 03/06/10
% Last Modified: 02/28/11
%% Description
% comparison
%
%
%% Updates
% Modified 10/18/10 to incldue repression of ectopic expression.
% Modified to hack failed combine data code
% Modified 12/09/10 to add new datasets and correct combining of slides.
% Modified 02/28/11 to use cityscape and cumulitive sum plots.
%% Source Code
clear all;
folder = '/Volumes/Data/Lab Data/Shadow_data/Processed';
data_folder = '/Users/alistair/Documents/Berkeley/Levine_Lab/Projects/Shadow Enhancers/Code_Data/';
emb_roots = {'MP09_22C_y_hb'; % 1
'MP02_22C_y_hb'; % 2
'MP02_30C_y_hb';% 3
'MP02_30C_LacZ_hb';% 4 % yes it's actually yellow
'MP01_22C_y_hb'; % 5
'BAC09_22C_y_hb'; % 6
'BAC09_30C_y_hb';% 7
'BAC01_30C_y_hb';% 8
'BAC02_22C_y_hb'; % 9
'BAC01b_22C_y_hb';
'BAC01b_30C_y_hb';
'BAC02b_30C_y_hb';
};
%1 +6, 2+9, 3+4,
% % all names
% names = {'2 enhancers, 22C';
% 'no shadow, 22C';
% 'no shadow, 30C';
% 'no shadow, 30C, b';
% 'no primary, 22C';
% '2 enh 22C';
% '2 enh 30C';
% 'no primary 30C';
% 'no shadow, 22C, b';
% 'no primary 22C, b';
% 'no primary 30C, b';
% 'no shadow 30C, c'
% };
N = 150;
K = length(emb_roots);
% G= length(names);
age_table = cell(1,K);
miss_cnt = cell(1,K);
miss_rate = cell(1,K);
nd = cell(1,K);
lowon = cell(1,K);
cell_var = cell(1,K);
ectop_cnt = cell(1,K);
ectop_rate = cell(1,K);
endog_cnt = cell(1,K);
rept_cnt = cell(1,K);
for z=1:K
miss_cnt{z} = zeros(N,1);
miss_rate{z} = zeros(N,1);
lowon{z} = zeros(N,1);
nd{z} = zeros(N,1);
age_table{z} = cell(N,2);
ectop_cnt{z} = zeros(N,1);
ectop_rate{z} = zeros(N,1);
endog_cnt{z} = zeros(N,1);
rept_cnt{z} = zeros(N,1);
end
xmin = .2; xmax = .9; ymin = .15; ymax = .4;
% as fractions of the original image dimensions.
for z=1:K % k=2;
for n= 1:N
if n<10
emb = ['0',num2str(n)];
else
emb = num2str(n);
end
try
load([folder,'/',emb_roots{z},emb,'_data.mat']);
% get the indices of all nuclei in green that are not also red.
% require these nuclei also fall in the 'region' for red nuclei.
% s29_miss_cnt(n) = length(intersect(setdiff(pts2,pts1), ptr_nucin2));
% miss_cnt{z}(n) = length(intersect(setdiff(pts2,pts1), ptr_nucin2));
[miss_rate{z}(n), ptr_nucin2] = anlz_major_reg2(folder,emb_roots{z},emb );
% miss_rate{z}(n) = miss_cnt{z}(n)/length(pts2);
% lowon{z}(n) = lowon_fxn(H,handles,nin2,ptr_nucin2,emb);
endog_cnt{z}(n) = length(pts2);
rept_cnt{z}(n) = length(pts1);
ectop_cnt{z}(n) = length(intersect(setdiff(pts1,pts2),setdiff(ptr_nucin1,ptr_nucin2)'));
if length(H) > 2000
im_dim = 2048;
else
im_dim = 1024;
end
lims = round([xmin,xmax,ymin,ymax]*im_dim);
nd{z}(n) = NucDensity(cent,lims,0);
age_table{z}{n,1} = [folder,'/',emb_roots{z},emb,'_data.mat']; %
age_table{z}{n,2} = nd{z}(n);
ectop_rate{z}(n) = ectop_cnt{z}(n)/nd{z}(n);
catch ME
disp(ME.message);
%disp(['can not find file' folder,'/',emb_roots{z},emb,'_data.mat']);
end
end
end
close all;
save([data_folder, 'hb_SD-03-08-11']);
% save hb_SD-12-09-10
% save hb_SD-10-21-10;% includes ectopic repression analysis
% save hb_SD-10-18-10;% includes ectopic repression analysis
% save hb_SD-10-13-10;
% save hb_SD-9-13-10
% save hb_shadow_yellow_data; % load hb_shadow_yellow_data;
% clear all; load hb_SD-10-21-10;
%1 +6, 2+9, 3+4,
%%
clear all;
data_folder = '/Users/alistair/Documents/Berkeley/Levine_Lab/Projects/Shadow Enhancers/Code_Data/';
%load([data_folder,'hb_SD-12-09-10']);
load([data_folder, 'hb_SD-03-08-11']);
% Merge data
% %
% % all names
% names = {'2 enhancers, 22C'; % 1
% 'no shadow, 22C'; % 2
% 'no shadow, 30C'; % 3
% 'no shadow, 30C, b'; % 4
% 'no primary, 22C'; % 5
% '2 enh 22C'; % 6
% '2 enh 30C'; % 7
% 'no primary 30C'; % 8
% 'no shadow, 22C, b'; % 9
% 'no primary 22C, b'; % 10
% 'no primary 30C, b'; % 11
% 'no shadow 30C, c' % 12
% };
Nnuc = cell(1,6); foff = cell(1,6);
foff{1} = [miss_rate{1}; miss_rate{6}] ; Nnuc{1} = [nd{1}; nd{6}] ; % 2 enhancer 22C
ect{1} = [ectop_rate{1}; ectop_rate{6}] ;
foff{2} = miss_rate{7}; Nnuc{2} = nd{7}; % 2 enhancer 30C
ect{2} = ectop_rate{7} ;
foff{3} = [miss_rate{2}; miss_rate{9}]; Nnuc{3} = [nd{2}; nd{9}]; % no shadow 22C
%foff{3} = [miss_rate{2}]; Nnuc{3} = [nd{2}]; % no shadow 22C
ect{3} = [ectop_rate{2}; ectop_rate{9}] ;
foff{4} = [miss_rate{3}; miss_rate{4}; miss_rate{12}]; Nnuc{4} = [nd{3}; nd{4}; nd{12}]; % no shadow 30C
ect{4} = [ectop_rate{3}; ectop_rate{4}; ectop_rate{12}];
foff{5} = [miss_rate{5}; miss_rate{10}]; Nnuc{5} = [nd{5}; nd{10}]; % no primary 22C
%foff{5} = [miss_rate{5}]; Nnuc{5} = [nd{5}]; % no primary 22C
ect{5} = [ectop_rate{5}; ectop_rate{10}];
foff{6} = [miss_rate{8}; miss_rate{11}]; Nnuc{6} = [nd{8}; nd{11}]; % no primary 30C
ect{6} = [ectop_rate{8}; ectop_rate{11}];
G = length(foff);
for k=1:G
data = nonzeros(foff{k});
foff{k} = [data; zeros(200-length(data),1)];
data = nonzeros(Nnuc{k});
Nnuc{k} = [data; zeros(200-length(data),1)];
end
names = {'control 22C';
'control 30C';
'no distal 22C';
'no distal 30C';
'no proximal 22C';
'no proximal 30C'
};
%%
%ND = cell2mat(nd);
ND = cell2mat(Nnuc);
age_offset = 4.8;
emb_cycle = age_offset + log2( nonzeros( sort(ND(:)) ) );
figure(2); clf; plot( emb_cycle ,'r.');
title(['hb embryos, N = ',num2str(length(nonzeros(ND(:))) ) ],'FontSize',15);
set(gca,'FontSize',15); grid on;
set(gcf,'color','w'); ylabel('log_2(nuc density)'); xlabel('embryo number');
ylim([10,14.99]);
%%
G= length(names);
cc14 =cell(1,G); cc13 = cell(1,G); cc12 = cell(1,G); cc11 = cell(1,G); cc10 = cell(1,G); cc9 = cell(1,G);
for z=1:G
logage = age_offset + log2( ND(:,z) );
cc14{z} = logage >14;
cc13{z} = logage <14 & logage> 13;
cc12{z} = logage <13 & logage > 12;
cc11{z} = logage <12 & logage > 0 ;
foff{z}(foff{z}==Inf) = 0;
end
%% Plot Fraction of missing nuclei distributions
xlab = 'fraction of missed nuclei';
F = 12; % FontSize;
labs = {'30C','22C'};
co = [1,3,5]; ho = [2,4,6];
plot_miss = cell(1,G);
for k=1:G; plot_miss{k} = foff{k}(cc13{k}); end
% Look at just 22C data
data = plot_miss(co); Names = names(co);
% data = plot_miss(ho); names = names(ho); % 30C data
Ts = length(data);% number of tracks
pW = zeros(Ts);
pA = zeros(Ts);
for i=1:Ts
for j = 1:Ts
pW(i,j) = ranksum(data{i},data{j}); % Wilcox Rank Sum
pA(i,j)=anovan([data{i}',data{j}'],{[zeros(1,length(data{i})),ones(1,length(data{j}))]},'display','off'); % 2-way ANOVA
end
end
Wpvals = ['p_{12} = ',num2str(pW(1,2),2), ' p_{13} = ',num2str(pW(1,3),2) , ' p_{23} = ',num2str(pW(2,3),2) ];
Apvals = ['p_{12} = ',num2str(pA(1,2),2), ' p_{13} = ',num2str(pA(1,3),2) , ' p_{23} = ',num2str(pA(2,3),2) ];
disp(['2-way Anova: ', Apvals]);
figure(1); clf;
cityscape(data,Names,xlab,F);
figure(3); clf;
cumhist(data,Names,xlab,F);
title(['pairwise Wilcoxon: ' Wpvals]);
set(gcf,'color','w');
disp([names{1}, ': ' ,num2str(median([data{1}])),'+/-',num2str(std([data{1}])), ' missing']);
disp([names{2}, ': ' ,num2str(median([data{2}])),'+/-',num2str(std([data{2}])), ' missing']);
disp([names{3}, ': ' ,num2str(median([data{3}])),'+/-',num2str(std([data{3}])), ' missing']);
% ranksum(data{1}, MP09_22Cect)
anovan([data{1}',MP09_22Cect'],{[zeros(1,length(data{1})),ones(1,length(MP09_22Cect))]},'display','off')
%% Plot Expression variability.
xlab = 'fraction of missed nuclei';
F = 12; % FontSize;
labs = {'30C','22C'};
co = [1,3,5]; ho = [2,4,6];
plot_miss = cell(1,G);
for k=1:G; plot_miss{k} = foff{k}(cc13{k}); end
% Look at just 22C data
data = plot_miss(ho); Names = names(ho);
data{1} = data{1} - median(data{1}) + .5;
data{2} = data{2} - median(data{2})+ .5;
data{3} = data{3} - median(data{3})+ .5;
% data = plot_miss(ho); names = names(ho); % 30C data
Ts = length(data);% number of tracks
pW = zeros(Ts);
pA = zeros(Ts);
for i=1:Ts
for j = 1:Ts
pW(i,j) = ranksum(data{i},data{j}); % Wilcox Rank Sum
pA(i,j)=anovan([data{i}',data{j}'],{[zeros(1,length(data{i})),ones(1,length(data{j}))]},'display','off'); % 2-way ANOVA
end
end
Wpvals = ['p_{12} = ',num2str(pW(1,2),2), ' p_{13} = ',num2str(pW(1,3),2) , ' p_{23} = ',num2str(pW(2,3),2) ];
Apvals = ['p_{12} = ',num2str(pA(1,2),2), ' p_{13} = ',num2str(pA(1,3),2) , ' p_{23} = ',num2str(pA(2,3),2) ];
disp(['2-way Anova: ', Apvals]);
figure(3); clf;
cumhist(data,Names,xlab,F);
title(['pairwise Wilcoxon: ' Wpvals]);
set(gcf,'color','w');
disp([names{1}, ': ' ,num2str(median([data{1}])),'+/-',num2str(std([data{1}])), ' missing']);
disp([names{2}, ': ' ,num2str(median([data{2}])),'+/-',num2str(std([data{2}])), ' missing']);
disp([names{3}, ': ' ,num2str(median([data{3}])),'+/-',num2str(std([data{3}])), ' missing']);
% ranksum(data{1}, MP09_22Cect)
% anovan([data{1}',MP09_22Cect'],{[zeros(1,length(data{1})),ones(1,length(MP09_22Cect))]},'display','off')
%% Ectopic expression rate
xlab = 'ectopic expression rate';
names = {'control 22C';
'control 30C';
'no shadow 22C';
'no shadow 30C';
'no primary 22C';
'no primary 30C'
};
plot_miss = cell(1,G);
for k=1:G; plot_miss{k} = ect{k}(cc13{k}); end
data = plot_miss;
Ts = length(data);% number of tracks
pW = zeros(Ts);
pA = zeros(Ts);
for i=1:Ts
for j = 1:Ts
pW(i,j) = ranksum(data{i},data{j}); % Wilcox Rank Sum
pA(i,j)=anovan([data{i}',data{j}'],{[zeros(1,length(data{i})),ones(1,length(data{j}))]},'display','off'); % 2-way ANOVA
end
end
Wpvals = ['p_{12} = ',num2str(pW(1,2),2), ' p_{13} = ',num2str(pW(1,3),2) , ' p_{23} = ',num2str(pW(2,3),2) ];
Apvals = ['p_{12} = ',num2str(pA(1,2),2), ' p_{13} = ',num2str(pA(1,3),2) , ' p_{23} = ',num2str(pA(2,3),2) ];
disp(['pairwise Wilcoxon rank sum: ', Wpvals]);
disp(['2-way ANOVA: ',Apvals]);
figure(2); clf;
cityscape(data,names,xlab,F);
figure(4); clf;
cumhist(data,names,xlab,F);
title(['pairwise Wilcoxon: ' Wpvals]);
set(gcf,'color','w');
MP09_22Cect = data{1};
MP09_30Cect = data{2};
disp([names{1}, ': ' ,num2str(median([data{1}])),'+/-',num2str(std([data{1}])), ' missing']);
disp([names{2}, ': ' ,num2str(median([data{2}])),'+/-',num2str(std([data{2}])), ' missing']);
disp([names{3}, ': ' ,num2str(median([data{3}])),'+/-',num2str(std([data{3}])), ' missing']);
disp([names{4}, ': ' ,num2str(median([data{4}])),'+/-',num2str(std([data{4}])), ' missing']);
disp([names{5}, ': ' ,num2str(median([data{5}])),'+/-',num2str(std([data{5}])), ' missing']);
disp([names{6}, ': ' ,num2str(median([data{6}])),'+/-',num2str(std([data{6}])), ' missing']);