Added source Matlab code for reference

matlab/linkage/makecomplete.m

@@ -0,0 +1,70 @@
+function [data, totalmissing] = makecomplete(data)
+%MAKECOMPLETE ESTIMATING missing alleles in a loci. 
+%   Input: 
+%     data: a baps data format, e.g. last column is index. Missing values
+%     are denoted as any non-positive integers, commonly as 0 or -999.
+
+
+[nrows, ncols] = size(data);
+id = all(data>0);
+if all(id) % no missing values
+    return 
+else
+    fprintf(1,'Estimating the missing values...');
+    
+    % remove the totally missing loci
+    missingloci = find(id==0);
+    totalmissing = find(all(data(:,missingloci)<=0));
+    if ~isempty(totalmissing) 
+        disp('Totally missing loci were found.');
+        data(:,missingloci(totalmissing)) = ones(nrows,length(totalmissing));
+    end
+%     goodloci = setdiff([1:ncols],missingloci(totalmissing));
+%     data = data(:,goodloci);
+%     missingloci = find(all(data>0)==0);
+    
+    data_in = data(:,[missingloci end]);
+    [counts,noalle,prior,adjprior,rawalleles,data_in] = allfreqsnew3(data_in);
+    data(:,missingloci) = data_in(:,[1:end-1]);
+    
+    s_counts = sum(counts,3);
+%     m_counts = size(counts,3)*ones(1, size(counts,2)) - sum(s_counts); % counts of missing values
+    m_counts = nrows*ones(1, size(counts,2)) - sum(s_counts); % counts of missing values
+    m = repmat(m_counts,size(s_counts,1),1);
+    a = s_counts + prior;
+    a = a./repmat(sum(a),size(a,1),1);
+    c = round(m.*a);
+    
+    % Be sure that the sum matches
+    reassign = find(sum(c)~=m_counts);
+    for i = reassign
+        dif = sum(c(:,i)) - m_counts(:,i);
+        if dif > 0
+            remove = find(c(:,i)==max(c(:,i)));
+            c(remove(1),i)=c(remove(1),i) - dif; % decrease by the diff
+        else
+            add = find(c(:,i)==min(c(:,i)));
+            c(add(1),i)=c(add(1),i) - dif; % increase by the diff
+        end
+    end
+    try
+    % Fill in the missing values    
+    for i = 1:length(missingloci)
+        missingrows = find(data(:,missingloci(i))<=0);
+        p = randperm(m_counts(i));
+        cum = [0 cumsum(c(:,i))'];
+        for j = 1:size(c,1)
+            data(missingrows(p([cum(j)+1:cum(j+1)])),missingloci(i)) = j;
+        end
+    end
+    catch
+        % disp('*** ERROR: in completing the missing data.');
+        data = [];
+        totalmissing = [];
+        return
+    end
+    fprintf(1,'Finished.\n');
+end
+
+
+