add source code for main function

src/Assignment.m

@@ -0,0 +1,41 @@
+function [reAssignClassall,reAssignClasstop3]=Assignment(kmeandata,regulators,Assign)
+%UNTITLED2 Summary of this function goes here
+%   Detailed explanation goes here
+num=unique(kmeandata(:,2));
+moduleall=[];
+moduletop3=[];
+for nummod=1:size(num,1)
+    %data=kmeandata(find(kmeandata(:,2)==nummod),:);
+    group_struct=Assign{nummod};
+scoremoduleall=[];
+scoremoduletop3=[];
+for i=1:size(kmeandata,1)
+    geneID=kmeandata(i,1);
+    scoreall=0;
+    scoretop3=[];
+    for j=1:size(group_struct,2)
+        %gene=group_struct(j).data(find(group_struct(j).data(:,1)==geneID),3:end);
+        gene=kmeandata(find(kmeandata(:,1)==geneID),group_struct(j).conditions);
+        scrdata=sum(sum(-(gene-group_struct(j).mean).^2/(2*group_struct(j).std^2)-log(group_struct(j).std)));
+        scoreall=scoreall+scrdata;
+        scoretop3=[scoretop3;scrdata];
+    end;
+    n=size(scoretop3,1);
+    scoretop3=sort(scoretop3);
+    scoremoduleall=[scoremoduleall;kmeandata(i,1:2) scoreall];
+    scoremoduletop3=[scoremoduletop3;kmeandata(i,1:2) sum(scoretop3(n-2:n,:))];
+end;
+    moduleall=[moduleall scoremoduleall(:,3)];
+    moduletop3=[moduletop3 scoremoduletop3(:,3)];
+end;
+    moduleall=[kmeandata(:,1:2) moduleall];
+    moduletop3=[kmeandata(:,1:2) moduletop3];
+    reAssignClassall=[];
+    reAssignClasstop3=[];
+    for ii=1:size(kmeandata,1)
+        reAssignClassall=[reAssignClassall;moduleall(ii,1:2) find(moduleall(ii,:)==max(moduleall(ii,3:end)))-2 moduleall(ii,3:end)];
+        reAssignClasstop3=[reAssignClasstop3;moduletop3(ii,1:2) find(moduletop3(ii,:)==max(moduletop3(ii,3:end)))-2 moduletop3(ii,3:end)];
+    end;
+
+
+

src/assignmentgene.m

@@ -0,0 +1,49 @@
+function [Assign]=assignmentgene(data,regulators,Depth)
+%UNTITLED Summary of this function goes here
+%   Detailed explanation goes here
+assignmatrixall=[];
+assignmatrixtop3=[];
+num=unique(data(:,2));
+ Assign={};
+ for i=1:size(num,1)
+     datamodule=data(find(data(:,2)==num(i)),:);
+     datamodule=[[1:size(data,2)];datamodule];
+ %     [scoremoduleall,scoremoduletop3]=treeTraining3Score(datamodule,regulators,Depth)
+ %     assignmatrixall=scoremoduleall;
+ %     assignmatrixtop3=scoremoduletop3;
+     [tree,treegene,treeMV,group_struct]=treeTraining3(datamodule,regulators,Depth);
+     Assign{i}=group_struct;
+ end;
+ %save Assign Assign;
+
+% v6=[];
+% left=[];
+% right=[];
+% row={};
+% for num=1:size(matrix,2) %暂时不考虑叶子结点重复出现同一个转录因子的情况
+%     if (matrix(5,num)==matrix(5,num+1) & ~isnan(matrix(5,num)))
+%         row=[row;num];
+%         v6=matrix(6,find(matrix(5,:)==matrix(5,num)));
+%         if(matrix(6,num)==v6[1,1])
+%             left=[left;matrix(5,num) matrix(7,num)];
+%         elseif(matrix(6,num)!=v6[1,1] & ~isnan(matrix(6,num)))
+%             right=[right;matrix(5,num) matrix(7,num)];
+%         end;
+%     elseif ()
+%     end;
+
+
+
+% number=unique(tree(5,~isnan(tree(5,:))));
+% 
+% for j=1:size(number,2)
+%     matrix(7,find(matrix(5,:)==number(1,j)));
+%     if (number(1,j)>0)
+% for i=2:size(data,1)
+%     gene=data(i,3:end);
+%     scrdataup=sum(sum(-(geneup-meandataup).^2/(2*vardataup^2)-log(vardataup)));
+%     scrdatanonup=sum(sum(-(genenonup-meandatanonup).^2/(2*vardatanonup^2)-log(vardatanonup)));
+%     scoreupall=scrdataup+scrdatanonup;
+% end
+
+

src/choosedregulator.m

@@ -0,0 +1,19 @@
+function [regulatorID,up_or_down,score]=choosedregulator(data,regulators)
+%UNTITLED2 Summary of this function goes here
+%   Detailed explanation goes here
+reg=[];
+MV=[];
+for i=1:size(regulators,1);
+    [meanvar,regulascore]=scorefunction(data,regulators(i,:));
+    reg=[reg;regulascore meanvar];
+
+end;
+    reg=sortrows(reg,4);
+    regulatorID=reg(end,1);
+    up_or_down=reg(end,5);
+    score=reg(end,4);
+    MV=[regulatorID reg(end,6:end)];
+    save MV MV;
+
+
+

src/correlationAnalysis.m

@@ -0,0 +1,13 @@
+function [corrscore]=correlationAnalysis(assign)
+corrscore=[];
+for i=1:size(assign,2)
+        data=[];
+    for j=1:size(assign{1,i},2)
+        data=[data assign{1,i}(1,j).data(2:end,3:end)];
+    end;
+    b=corr(data');
+    u=b-eye(size(data',2));
+    s=triu(u);
+    M=sum(sum(s))*2/size(data',2)/(size(data',2)-1);
+    corrscore=[corrscore;i M];
+end;

src/dataforperl.m

@@ -0,0 +1,7 @@
+function [moduledata]=dataforperl(Assigndata14con7level2)
+
+moduledata=[];
+for i=1:size(Assigndata14con7level2,2)
+    i
+moduledata=[moduledata;Assigndata14con7level2{1,i}(1,1).data(2:end,1:2)];
+end;

src/draw.m

@@ -0,0 +1,6 @@
+function [tfnet]=draw(DataSy,assign,regulatorid,regulatorname)
+tfnet=[];
+[sDataSy]=regulaorderbycon(assign);
+[m]=smallcodes(sDataSy,DataSy);
+res=getLevelOfReg(assign);
+tfnet=picmodule(sDataSy,m,assign,regulatorid,regulatorname,res,DataSy)