'python wrapper to run retropath2.0 knime workflow'
Project description
Retropath2.0 wrapper
Implementation of the KNIME retropath2.0 workflow. Takes for input the minimal (dmin) and maximal (dmax) diameter for the reaction rules and the maximal path length (maxSteps). The tool expects the following files: rules.csv
, sink.csv
and source.csv
and produces results in an output folder.
Input
Required:
- sink_file: (string) Path to the collection of chemical species to finish metabolic route exploration
- source_file: (string) Path to the target compound desired to be synthesised
- rules_file: (string) Path to the reaction rules
Optional:
- --outdir: (string, default='out') Path to the folder where result files are written
- --knime_exec: (integer, default=9999) Path to Knime exec file
- --max_steps : (integer, default='3') Maximal number of steps
- --topx : (integer, default: 100) For each iteration, number of rules
- --dmin : (integer, default: 0)
- --dmax : (integer, default: 1000)
- --mwmax_source : (integer, default: 1000)
- --mwmax_cof : (integer, default: 1000)
- --timeout : (integer, default: 30) Timeout in minutes
- --is_forward : (bool, default: False) Forward or reverse synthesis
Prerequisites
- Python 3
- KNIME (code was tested on 3.6.2 version)
Install
From pip
retropath2_wrapper requires Knime which is not available through pip. The 3.6.2 version will be downloaded if not already installed.
[sudo] python -m pip install retropath2_wrapper
From Conda
[sudo] conda install -c brsynth retropath2_wrapper
Run
retropath2_wrapper process
From Python code
from retropath2_wrapper import run, build_args_parser
parser = build_args_parser()
args = parser.parse_args()
run(args.sinkfile,
args.sourcefile,
args.rulesfile)
From CLI
python -m retropath2_wrapper sinkfile.csv sourcefile.csv rulesfile.csv
Test
All modes can be tested with:
cd tests
./test-in-docker.sh
How to cite RetroPath2.0?
Please cite:
Delépine B, Duigou T, Carbonell P, Faulon JL. RetroPath2.0: A retrosynthesis workflow for metabolic engineers. Metabolic Engineering, 45: 158-170, 2018. DOI: https://doi.org/10.1016/j.ymben.2017.12.002
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