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-% Quikr multifasta->otu_table_(for_qiime_use) wrapper code written by Gail Rosen -- 2/1/2013

-%This is an example of how to run Multifasta Quikr with a custom 

-%training database (in this case Greengenes OTU's within 94% identity)

-

-%make sure Matlab/Octave is in your path

-%cd /path/to/Quikr

-

-%User-defined variables

-input_directory='py-quikr/input/'; %path to input directory of samples

-output_directory='quikr_results'; %path to where want output files to go

-otu_table_name='gg1194_otu_octave.txt'; %name of output otu_table filename

-trainingdatabasefilename='gg_94_otus_4feb2011.fasta'; %full path to the FASTA file you wish to use as a training database

-k=6; %pick a k-mer size

-addpath('quikr-code');

-

-% make output directory

-mkdir([output_directory]);

-

-% get a list of the input directory

-

-thedirs=dir([input_directory]);

-thetime=zeros(numel(thedirs)-1,1);

-names={};

-

-tic();

-

-trainingmatrix=quikrTrain(trainingdatabasefilename,k); %this will return the training database

-disp('Training time:')

-[headers,~]=fastaread(trainingdatabasefilename); %read in the training database

-lambda=10000; 

-training_time=toc()

-

-species=struct();

-keys={};

-

-tic();

-

-

-i=0;

-%for numdirs=3:5

-for numdirs=3:numel(thedirs)

-i=i+1;

-disp([num2str(i) ' out of ' num2str(numel(thedirs)-2)])

-fastafilename=[input_directory '/' thedirs(numdirs).name];

-[loadfasta,~]=fastaread(fastafilename);

-numreads=numel(loadfasta);

-xstar=quikrCustomTrained(trainingmatrix,fastafilename,k,lambda);

-

-nonzeroentries=find(xstar); %get the indicies of the sequences quikr predicts are in your sample

-proportionscell=num2cell(xstar(nonzeroentries)); %convert the concentrations into a cell array

-namescell=headers(nonzeroentries); %Get the names of the sequences

-namesandproportions={namescell{:}; proportionscell{:}}; %This cell array contains the (unsorted) names of the reconstructed sequences and their concentrations (in the first and second columns respectively)

-

-[a cols]=size(namesandproportions);

-amount=zeros(cols,1);

-for j=1:cols

-  names{j}=['s' namesandproportions{1,j}];

-  amount(j)=namesandproportions{2,j};

-  if strcmp(keys,names{j})

-	temp=species.(names{j});

-      	temp(i)=round(amount(j).*numreads);

-      	species.(names{j})=temp;

-  else

-      temp=zeros(numel(thedirs)-3+1,1);

-      temp(i)=round(amount(j).*numreads);

-      if temp(i)==0

-         %insignificant counts, do nothing

-      else

-         species.(names{j})=temp;

-         keys{end+1}=names{j};

-      end

-  end

-end

-

-thefa=strfind(thedirs(numdirs).name,'.fa');

-

-if ~isempty(thedirs(numdirs).name(1:thefa-1))

-	sampleid{i}=thedirs(numdirs).name(1:thefa-1);

-else

-	sampleid{i}='empty_sampleid';

-end

-

-thetime(i+1)=toc();

-thetime(i+1)

-

-end

-

-disp('Total time to compute Quikr:')

-toc()

-disp('Quikr Average time per file:')

-mean(diff(thetime(1:i+1)))

-

-tic()

-numits=i;

-

-fid=fopen([output_directory '/' otu_table_name],'w');

-

-% insert our header

-fprintf(fid,'# QIIME vGail OTU table\n');

-fprintf(fid,'#OTU_ID\t');

-for i=1:numits

-  if i<numits

-    fprintf(fid,'%s\t',sampleid{i});

-  else

-    fprintf(fid,'%s',sampleid{i});

-  end

-end

-

-fprintf(fid,'\n');

-%

-

-

-% print our key and our values for each keys

-for k=1:numel(keys)

-  fprintf(fid,'%s',keys{k}(2:end))

-  temp(:,k)=species.(keys{k});

- 

-  for i=1:numits

-    fprintf(fid,'\t%d',temp(i,k));

-  end

-  

-  fprintf(fid,'\n');

-end

-

-fclose(fid);

-

-disp('Time to output OTU Table:')

-toc()

-