Added source Matlab code for reference

matlab/independent/preprocessXLS.m

@@ -0,0 +1,177 @@
+function c = preprocessXLS(xlsfile,varargin)
+% This function preprocesses the input xlsfile
+% File structure:  first line - title
+%                  else - first column, name of individuals
+%                       - second to end column, sequences of the given genes
+
+% Lu Cheng, 16.02.2010
+
+%% check file names
+
+file_suff = '.xls'; % endings of the input file
+if ~(exist(xlsfile,'file')==2)
+    fprintf('Input file %s does not exists, quit!\n',xlsfile);
+    return;
+end
+
+if ~strcmp(xlsfile(end-length(file_suff)+1:end),file_suff)
+    fprintf('Input file %s does not end with %s, quit!\n',xlsfile,file_suff);
+    return;
+end
+
+%% process the xls file
+
+% Here we assume there is no missing values, if so, the missing values are
+% indicated by 0
+[data, component_mat, popnames] = processxls(xlsfile);
+
+% missing data 0 is transformed to |alphabet|+1, in the [ACGT] case, '-' is 5
+[data, rowsFromInd, alleleCodes, noalle, adjprior, priorTerm] = handleData(data);
+
+c.data = data; c.rowsFromInd = rowsFromInd;
+c.alleleCodes = alleleCodes; c.noalle=noalle;
+c.adjprior = adjprior;
+% c.priorTerm = c.priorTerm;
+
+c.component_mat = component_mat;
+c.popnames = popnames;
+
+%% count the cliques and separators
+
+index = data(:,end);
+
+if isempty(varargin)
+    [data_clique, data_separator, noalle_clique, noalle_separator, codes_cq, codes_sp, info_cq_loci, info_sp_loci] = ...
+        transform5(data, component_mat);
+else
+    c_train = varargin{1};
+    
+    if ~all(all(c_train.component_mat == component_mat))
+        disp('The gene lengths are different between the training data and the test data!');
+        return;
+    end
+    
+    [data_clique, data_separator, noalle_clique, noalle_separator, codes_cq, codes_sp, info_cq_loci, info_sp_loci] = ...
+        transform5(data, component_mat, c_train.info_cq_loci,c_train.info_sp_loci);
+end
+data_clique = [data_clique index];
+data_separator = [data_separator index];
+
+% Count the data, note that the order of the alphabets keeps the same
+[counts_cq, nalleles_cq, prior_cq, adjprior_cq, genotypes_cq] ...
+    = allfreqsnew2(data_clique, double(noalle_clique));
+[counts_sp, nalleles_sp, prior_sp, adjprior_sp, genotypes_sp] ...
+    = allfreqsnew2(data_separator, double(noalle_separator));
+
+clear prior_cq prior_sp nalleles_cq nalleles_sp genotypes_cq genotypes_sp;
+
+counts_cq = uint16(counts_cq);
+counts_sp = uint16(counts_sp);
+
+c.counts_cq = counts_cq;
+c.counts_sp = counts_sp;
+
+c.adjprior_cq = adjprior_cq;
+c.adjprior_sp = adjprior_sp;
+
+c.codes_cq = codes_cq;
+c.codes_sp = codes_sp;
+
+c.info_cq_loci = info_cq_loci;
+c.info_sp_loci = info_sp_loci;
+
+%--------------------------------------------------------------------------
+function [newData, rowsFromInd, alleleCodes, noalle, adjprior, priorTerm] = handleData(raw_data)
+% Alkuperäisen datan viimeinen sarake kertoo, miltä yksilöltä
+% kyseinen rivi on peräisin. Funktio tutkii ensin, että montako
+% riviä maksimissaan on peräisin yhdeltä yksilöltä, jolloin saadaan
+% tietää onko kyseessä haploidi, diploidi jne... Tämän jälkeen funktio
+% lisää tyhjiä rivejä niille yksilöille, joilta on peräisin vähemmän
+% rivejä kuin maksimimäärä.
+%   Mikäli jonkin alleelin koodi on =0, funktio muuttaa tämän alleelin
+% koodi pienimmäksi koodiksi, joka isompi kuin mikään käytössä oleva koodi.
+% Tämän jälkeen funktio muuttaa alleelikoodit siten, että yhden lokuksen j
+% koodit saavat arvoja välillä 1,...,noalle(j).
+
+% English Comments added 
+% Small modifications have been added
+% Lu Cheng, 17.02.2010
+
+% Last column are the indexes of the samples, the raw_data is supposed to
+% be unit16 type, 0 indicates missing value
+data = raw_data;
+nloci=size(raw_data,2)-1;
+
+% Replace missing value with the |alphabet|+1, thus 0 is replaced by 5 for
+% DNA dataset
+dataApu = data(:,1:nloci);
+nollat = find(dataApu==0);
+if ~isempty(nollat)
+    isoinAlleeli = max(max(dataApu));
+    dataApu(nollat) = isoinAlleeli+1;
+    data(:,1:nloci) = dataApu;
+end
+
+% stores all different alleles at each loci, construct the allle codes matrix
+noalle=zeros(1,nloci);
+alleelitLokuksessa = cell(nloci,1);
+for i=1:nloci
+    alleelitLokuksessaI = unique(data(:,i));
+    alleelitLokuksessa{i,1} = alleelitLokuksessaI(logical(alleelitLokuksessaI>=0));
+    noalle(i) = length(alleelitLokuksessa{i,1});
+end
+alleleCodes = zeros(max(noalle),nloci);
+for i=1:nloci
+    alleelitLokuksessaI = alleelitLokuksessa{i,1};
+    puuttuvia = max(noalle)-length(alleelitLokuksessaI);
+    alleleCodes(:,i) = [alleelitLokuksessaI; zeros(puuttuvia,1)];
+end
+
+%-----------------modified by Lu Cheng 17.02.2010--------------------------%
+% NOTE: Here we do not want to change the alpahbets, thus the following
+% lines are commented
+
+% replace the index of an allele to replace the allele
+% for loc = 1:nloci
+%     for all = 1:noalle(loc)
+%         data(logical(data(:,loc)==alleleCodes(all,loc)), loc)=all;
+%     end;
+% end;
+%-----------------modified end.....----------------------------------------%
+
+% handle diploid situation
+nind = max(data(:,end));
+nrows = size(data,1);
+ncols = size(data,2);
+rowsFromInd = zeros(nind,1);
+for i=1:nind
+    rowsFromInd(i) = length(find(data(:,end)==i));
+end
+maxRowsFromInd = max(rowsFromInd);
+a = -999;
+emptyRow = repmat(a, 1, ncols);
+lessThanMax = find(rowsFromInd < maxRowsFromInd);
+missingRows = maxRowsFromInd*nind - nrows;
+data = [data; zeros(missingRows, ncols)];
+pointer = 1;
+for ind=lessThanMax'    %Käy läpi ne yksilöt, joilta puuttuu rivejä
+    miss = maxRowsFromInd-rowsFromInd(ind);  % Tältä yksilöltä puuttuvien lkm.
+    for j=1:miss
+        rowToBeAdded = emptyRow;
+        rowToBeAdded(end) = ind;
+        data(nrows+pointer, :) = rowToBeAdded;
+        pointer = pointer+1;
+    end
+end
+data = sortrows(data, ncols);   % Sorttaa yksilöiden mukaisesti
+newData = data;
+rowsFromInd = maxRowsFromInd;
+
+% calculate the prior for each loci, priorTerm is a constant term in the
+% formula, which is precalclulateed for speeding up the program
+adjprior = zeros(max(noalle),nloci);
+priorTerm = 0;
+for j=1:nloci
+    adjprior(:,j) = [repmat(1/noalle(j), [noalle(j),1]) ; ones(max(noalle)-noalle(j),1)];
+    priorTerm = priorTerm + noalle(j)*gammaln(1/noalle(j));
+end