updated documentation , added multi_gg_final.m

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+* Please name fasta files of sample reads with <sample id>.fa<*> and place them into one directory without any other file in that directory (for example, no hidden files that the operating system may generate, are allowed in that directory)
+* Note: When making your QIIME Metadata file, the sample id's must match the fasta file prefix names
+* Fasta files of reads must have a suffix that starts with .fa (e.g.: .fasta and .fa are valid while .fna is NOT)
+* Modify the top of the Matlab/Octave scripts for <input_directory>, <output_directory>, <output_filename>, and <training_database_filename>
+
+To use with QIIME, one must run the QIIME conversion tool on our OTU table output:
+convert_biom.py -i <quikr_otu_table.txt> -o <quikr_otu>.biom --biom_table_type="otu table"
+
+---------------------------
+
+4-step QIIME procedure after using Quikr to obtain 3D PCoA graphs:
+(Note: Our code works much better with WEIGHTED Unifrac as opposed to 
+Unweighted.)
+
+Pre-requisites: 1) <quikr_otu_table.txt>, 2) the tree of the database sequences that were used (e.g. 
+rdp7_mafft.fasttree, gg_94_otus_4feb2011.tre, etc.), and 3) your-defined <qiime_metadata_file.txt>
+
+1. convert_biom.py -i <quikr_otu_table.txt> -o <quikr_otu>.biom --biom_table_type="otu table"
+2. beta_diversity.py -i <quikr_otu>.biom -m weighted_unifrac -o beta_div -t <tree file (example: rdp7_mafft.fasttree)>
+3. principal_coordinates.py -i beta_div/weighted_unifrac_<quikr_otu>.txt -o <quikr_otu_project_name>_weighted.txt
+4. make_3d_plots.py -i <quikr_otu_project_name>_weighted.txt -o <3d_pcoa_plotdirectory> -m <qiime_metadata_file>
+