beta_diversity_through_plots.py – A workflow script for computing beta diversity distance matrices and the corresponding 3D plots

Description:

This script will perform beta diversity, principal coordinate anlalysis, and generate a preferences file along with 3D PCoA Plots.

Usage: beta_diversity_through_plots.py [options]

Input Arguments:

Note

[REQUIRED]

-i, --otu_table_fp

The input fasta file [REQUIRED]

-m, --mapping_fp

Path to the mapping file [REQUIRED]

-o, --output_dir

The output directory [REQUIRED]

[OPTIONAL]

-t, --tree_fp

Path to the tree file [default: None; REQUIRED for phylogenetic measures]

-p, --parameter_fp

Path to the parameter file, which specifies changes to the default behavior. See http://www.qiime.org/documentation/file_formats.html#qiime-parameters . [if omitted, default values will be used]

--color_by_all_fields

Plots will have coloring for all mapping fields [default: False; only include fields with greater than one value and fewer values than the number of samples]

-f, --force

Force overwrite of existing output directory (note: existing files in output_dir will not be removed) [default: None]

-w, --print_only

Print the commands but don’t call them – useful for debugging [default: False]

-a, --parallel

Run in parallel where available [default: False]

-e, --seqs_per_sample

Depth of coverage for even sampling [default: None]

--suppress_distance_histograms

Do not generate distance histograms [default: False]

--suppress_2d_plots

Do not generate 2D plots [default: False]

--suppress_3d_plots

Do not generate 3D plots [default: False]

-O, --jobs_to_start

Number of jobs to start. NOTE: you must also pass -a to run in parallel, this defines the number of jobs to be started if and only if -a is passed [default: 1]

Output:

This script results in a distance matrix (from beta_diversity.py), a principal coordinates file (from principal_coordinates.py), a preferences file (from make_prefs_file.py) and folder containing the resulting 3d PCoA plots (as an html from make_3d_plots.py).

Example:

The following steps are performed by the command below:

1. Compute a beta diversity distance matrix;
2. Peform a principle coordinates analysis on the result of Step 1;
3. Generate a 3D prefs file for optimized coloring of continuous variables;
4. Generate a 3D plot for all mapping fields with colors optimized for continuous data;
5. Generate a 3D plot for all mapping fields with colors optimized for discrete data.

beta_diversity_through_3d_plots.py -i otu_table.txt -o bdiv1 -t inseqs1_rep_set.tre -m inseqs1_mapping.txt -p custom_parameters.txt