parallel_beta_diversity.py – Parallel beta diversity

Description:

This script performs like the beta_diversity.py script, but is intended to make use of multicore/multiprocessor environments to perform analyses in parallel.

Usage: parallel_beta_diversity.py [options]

Input Arguments:

Note

[REQUIRED]

-i, --input_path

Input path, must be directory [REQUIRED]

-o, --output_path

Output path, must be directory [REQUIRED]

[OPTIONAL]

-m, --metrics

Beta-diversity metric(s) to use. A comma-separated list should be provided when multiple metrics are specified. [default: unweighted_unifrac,weighted_unifrac]

-t, --tree_path

Path to newick tree file, required for phylogenetic metrics [default: None]

-R, --retain_temp_files

Retain temporary files after runs complete (useful for debugging) [default: False]

-S, --suppress_submit_jobs

Only split input and write commands file - don’t submit jobs [default: False]

-T, --poll_directly

Poll directly for job completion rather than running poller as a separate job. If -T is specified this script will not return until all jobs have completed. [default: False]

-U, --cluster_jobs_fp

Path to cluster jobs script (defined in qiime_config) [default: start_parallel_jobs.py]

-W, --suppress_polling

Suppress polling of jobs and merging of results upon completion [default: False]

-X, --job_prefix

Job prefix [default: descriptive prefix + random chars]

-Z, --seconds_to_sleep

Number of seconds to sleep between checks for run completion when polling runs [default: 1]

-O, --jobs_to_start

Number of jobs to start [default: 4]

-f, --full_tree

By default, each job removes calls _fast_unifrac_setup to remove unused parts of the tree. pass -f if you already have a minimal tree, and this script will run faster

Output:

The output of %prog is a folder containing text files, each a distance matrix between samples.

Apply beta_diversity.py in parallel to multiple otu tables:

Apply the unweighted_unifrac and weighted_unifrac metrics (modify with -m) to all otu tables in rarefied_otu_tables (-i) and write the resulting output files to bdiv/ (-o, will be created if it doesn’t exist). Use the rep_set.tre (-t) to compute phylogenetic diversity metrics. ALWAYS SPECIFY ABSOLUTE FILE PATHS (absolute path represented here as $PWD, but will generally look something like /home/ubuntu/my_analysis/).

parallel_beta_diversity.py -i $PWD/rarefied_otu_tables/ -o $PWD/bdiv/ -t $PWD/rep_set.tre

Apply beta_diversity.py in parallel to a single otu table:

parallel_beta_diversity.py -i $PWD/otu_table.biom -o $PWD/bdiv_single/ -t $PWD/rep_set.tre