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Diffstat (limited to 'src/matlab/multifasta2otu/README')
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diff --git a/src/matlab/multifasta2otu/README b/src/matlab/multifasta2otu/README deleted file mode 100644 index 05a26c6..0000000 --- a/src/matlab/multifasta2otu/README +++ /dev/null @@ -1,27 +0,0 @@ -* Quikr multifasta->otu_table_(for_qiime_use) wrapper code written by Gail Rosen -- 2/1/2013 - -Usage tips: -* 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. they are in the data directory) -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> - |