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