Sampledata README

1. Assume the current directory is mydir/. After unzip and untar the rdp_classifier.tar.gz file into mydir, go to the direcoty rdp_classifier, you should have the following files or directories:
COPYRIGHT               docs                    rdp_classifier-version.jar  src
README                  lib                     sampledata
 
2. Create raw training data.
   You need to create two raw training files. There are two sample raw training data files in sampledata: testTaxonForQuerySeq.txt and testQuerySeq.fasta.
   -- testTaxonForQuerySeq.txt contains the hierarchical taxonomy information, taxon name and rank together is unique. The format looks like the following: 
	taxid*taxon name*parent taxid*depth*rank". 
	taxid, the parent taxid and depth should be in integer format. depth indicates the depth from the root taxon.
   -- testQuerySeq.fasta contains the raw training sequences labeled with lineage in fasta format. 
	The header of this fasta file starts with ">", followed by the sequence name, white space(s) and a list taxon names seperated by ';' with highest rank taxon first. 
	For example: >seq1 ROOT;Ph1;Fam1;G1;
    Note: a sequence can only be assigned to the lowest rank taxon.   

3. Create parsed training files from the raw training data.
   Assume two raw files are created in mydir/mydata: mytaxon.txt and mytrainseq.fasta.
   Run the command to create parsed training files:
   java -Xmx400m -cp rdp_classifier-2.0.jar edu/msu/cme/rdp/classifier/train/ClassifierTraineeMaker mydata/mytaxon.txt mydata/mytrainseq.fasta 1 version1 test mydata

    The first parameter "mydata/mytaxon.txt" contains the hierarchical taxonomy information.
    The second parameter "mydata/mytrainseq.fasta" contains the raw training sequences.
    The third parameter "1" is the trainset_no to mark the training files generated.
    The fourth parameter "version1" indicates the version of the hierarchical taxonomy.
    The fifth parameter "test" holds the modification information of the taxonomy.
    The fifth parameter 'mydata" specifies the output directory.

    Four parsed training files will be created and saved into directory mydata.
	bergeyTrainingTree.xml
	genus_wordConditionalProbList.txt
	logWordPrior.txt
	wordConditionalProbIndexArr.txt

4. Copy the property file sampledata/rRNAClassifier.properties to directory mydata.

5. Run command line class to classify sequences. Supported formats are Fasta, Genbank and EMBL.
   5a. Use the default training data to do classification:
	java -Xmx400m -jar rdp_classifier-2.0.jar sampledata/testQuerySeq.fasta testquery.out 

   5b. Use the user provided training data to do classification:
	java -Xmx400m -jar rdp_classifier-2.0.jar sampledata/testQuerySeq.fasta testquery.out  mydata/rRNAClassifier.properties

   The first parameter "sampledata/testQuerySeq.fasta" contains query sequences.
   The second parameter "testquery.out" is the output file.
   The third parameter "mydata/rRNAClassifier.properties" contains the mapping of the parsed training files..
