From 0594196bd9f9980e78d5560f6b16a756ad462e79 Mon Sep 17 00:00:00 2001
From: Calvin <calvin@EESI>
Date: Fri, 3 May 2013 16:33:46 -0400
Subject: added a contributor

---
 .../multifasta2otu/multifasta2otutable_gg1194.m    | 109 +++++++++++++++++++++
 1 file changed, 109 insertions(+)
 create mode 100644 src/matlab/multifasta2otu/multifasta2otutable_gg1194.m

(limited to 'src/matlab/multifasta2otu/multifasta2otutable_gg1194.m')

diff --git a/src/matlab/multifasta2otu/multifasta2otutable_gg1194.m b/src/matlab/multifasta2otu/multifasta2otutable_gg1194.m
new file mode 100644
index 0000000..a2872a4
--- /dev/null
+++ b/src/matlab/multifasta2otu/multifasta2otutable_gg1194.m
@@ -0,0 +1,109 @@
+%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='../../separated_samples'; %path to input directory of samples
+output_directory='quikr_results'; %path to where want output files to go
+otu_table_name='gg1194_otu_table.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
+
+
+mkdir([output_directory])
+thedirs=dir([input_directory]);
+thetime=zeros(numel(thedirs)-1,1);
+names={};
+
+
+tic()
+k=6; %pick a k-mer size
+trainingmatrix=quikrTrain(trainingdatabasefilename,k); %this will return the training database
+'Training time:'
+[headers,~]=fastaread(trainingdatabasefilename); %read in the training database
+lambda=10000; 
+training_time=toc()
+
+species=containers.Map;
+
+tic()
+
+
+i=0;
+%for numdirs=3:5
+for numdirs=3:numel(thedirs)
+i=i+1;
+[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}=namesandproportions{1,j};
+  amount(j)=namesandproportions{2,j};
+  if isKey(species,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);
+      species(names{j})=temp;
+  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
+
+'Total time to compute Quikr'
+toc()
+'Quickr Average time per file'
+mean(diff(thetime(1:i+1)))
+
+tic
+numits=i;
+
+fid=fopen([output_directory '/' otu_table_name],'w');
+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');
+
+thekeys=species.keys;
+for k=1:species.Count
+ fprintf(fid,'%s',thekeys{k})
+ temp(:,k)=species(thekeys{k});
+        for i=1:numits
+                fprintf(fid,'\t%d',temp(i,k));
+        end
+fprintf(fid,'\n');
+end
+fclose(fid);
+
+'Time to output OTU Table'
+toc
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