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| -rw-r--r-- | doc/matlab.markdown | 16 |
1 files changed, 10 insertions, 6 deletions
diff --git a/doc/matlab.markdown b/doc/matlab.markdown index ec9249c..09b0103 100644 --- a/doc/matlab.markdown +++ b/doc/matlab.markdown @@ -120,15 +120,15 @@ their concentrations (in the first and second columns respectively) Usage tips: * Please name fasta files of sample reads with <sample id>.fa<*> and place them - into one directory without any other f ile in that directory (for example, no + 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 - direct ory) + 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 <train ing_database_filename> +* 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: @@ -142,13 +142,17 @@ output: Unweighted.) Pre-requisites: -1. <quikr_otu_table.txt> +1. \<quikr\_otu\_table.txt\> 2. the tree of the database sequences that were used (e.g. dp7\_mafft.fasttree, gg\_94\_otus\_4feb2011.tre, etc.) -3. your-defined <qiime_metadata_file.txt> +3. your-defined \<qiime\_metadata\_file.txt> The QIIME procedue: + convert_biom.py -i <quikr_otu_table.txt> -o <quikr_otu>.biom --biom_table_type="otu table" + beta_diversity.py -i <quikr_otu>.biom -m weighted_unifrac -o beta_div -t <tree file> (example: rdp7_mafft.fasttree)> + principal_coordinates.py -i beta_div/weighted_unifrac_<quikr_otu>.txt -o <quikr_otu_project_name>_weighted.txt + make_3d_plots.py -i <quikr_otu_project_name>_weighted.txt -o <3d_pcoa_plotdirectory> -m <qiime_metadata_file> |