parallel_predict_traits.py – Runs predict_traits.py in parallel¶
Description:
Usage: parallel_predict_traits.py [options]
Input Arguments:
Note
[REQUIRED]
- -i, --observed_trait_table
- The input trait table describing directly observed traits (e.g. sequenced genomes) in tab-delimited format
- -t, --tree
- The full reference tree, in Newick format
- -o, --output_trait_table
- The output filepath for trait predictions
[OPTIONAL]
- -a, --calculate_accuracy_metrics
- If specified, calculate accuracy metrics (i.e. how accurate does PICRUSt expect its predictions to be?) and add to output file [default: False]
- -r, --reconstructed_trait_table
- The input trait table describing reconstructed traits (from ancestral_state_reconstruction.py) in tab-delimited format [default: None]
- --output_precalc_file_in_biom
- Instead of outputting the precalculated file in tab-delimited format (with otu ids as row ids and traits as columns) output the data in biom format (with otu as SampleIds and traits as ObservationIds) [default: False]
- -c, --reconstruction_confidence
- The input trait table describing confidence intervals for reconstructed traits (from ancestral_state_reconstruction.py) in tab-delimited format [default: None]
- -j, --parallel_method
- Method for parallelizaation. Valid choices are: sge, torque, multithreaded [default: multithreaded]
- -n, --num_jobs
- Number of jobs to be submitted. [default: 2]
- -d, --delay
- Number of seconds to pause between launching each job [default: 0]
- --already_calculated
- Precalculated file that is missing some otu predictions. Output will contain predictions from this file and the new predictions as well. [default: None]
Output:
Basic
parallel_predict_traits.py -i trait_table.tab -t reference_tree.newick -r asr_counts.tab -c asr_ci.tab -o predict_traits.tab