PICRUSt Script Index

Documentation for all PICRUSt scripts can be found here. This is a web version of the information that can be obtained for each script by calling the script with the -h parameter.

• ancestral_state_reconstruction.py – Runs ancestral state reconstruction given a tree and trait table
• categorize_by_function.py – Collapse table data to a specified level in a hierarchy.
• compare_biom.py – Compare the accuracy of biom files (expected and observed) either by observations (default) or by samples.
• download_picrust_files.py – Download PICRUSt precalculated files
• evaluate_test_datasets.py – Evaluate the accuracy of character predictions, given directories of expected vs. observed test results
• format_tree_and_trait_table.py – Formatting script for filtering and reformatting trees and trait tables.
• make_test_datasets.py – Generates test datasets for cross-validation studies of PICRUSt’s accuracy
• metagenome_contributions.py – This script partitions metagenome functional contributions according to function, OTU, and sample, for a given OTU table.
• normalize_by_copy_number.py – Normalize an OTU table by marker gene copy number
• parallel_predict_traits.py – Runs predict_traits.py in parallel
• pool_test_datasets.py – Pool character predictions within a directory, given directories of expected vs. observed test results
• predict_metagenomes.py – This script produces the actual metagenome functional predictions for a given OTU table.
• predict_traits.py – Given a tree and a set of known character states (observed traits and reconstructions), output predictions for unobserved character states
• print_picrust_config.py – Print out the PICRUSt config settings.
• run_genome_evaluations.py – Runs genome evaluations on PICRUSt.
• scale_metagenome.py – This script converts metagenomic relative abundance back to sequence counts, by scaling the relative abundnace of each gene in each sample in a biom file by a user-supplied sequencing depth
• start_parallel_jobs.py – Starts multiple jobs in parallel on multicore or multiprocessor systems.
• start_parallel_jobs_sge.py – Starts multiple jobs in parallel on SGE/qsub based multiprocessor systems.
• start_parallel_jobs_torque.py – Starts multiple jobs in parallel on Torque/qsub based multiprocessor systems.