'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.
Standalone
Prerequisites
- Python 3
Quick start
The main code is src/RetroPath2.py
and can be run as the following:
python src/RetroPath2.py \
-sinkfile <sink_file> \
-sourcefile <source_file> \
-max_steps 3 \
-rulesfile <rules_file> \
-topx 100 \
-dmin 0 \
-dmax 1000 \
-mwmax_source 1000 \
-mwmax_cof 1000 \
-timeout 30 \
-outdir <outdir_folder> \
-is_forward False
Docker
RetroPath2 can be run into a docker container.
Prerequisites
- Docker - Install
Installation
Before running the container, the image has to be built with:
cd docker
docker-compose build
Run
Then, the tool is runnable by:
cd docker
./RetroPath2.sh
-sinkfile <sink_file> \
-sourcefile <source_file> \
-max_steps 3 \
-rulesfile <rules_file> \
-topx 100 \
-dmin 0 \
-dmax 1000 \
-mwmax_source 1000 \
-mwmax_cof 1000 \
-timeout 30 \
-outdir <outdir_folder> \
-is_forward False
To call the tool with fresh code:
docker-compose run --rm -v <absolutepath_to_src>:/home/src retropath2
To call the tool from any location:
cd docker
docker-compose run --rm \
-v <path/to/source.csv>:/home/source.csv:ro \
-v <path/to/sink.csv>:/home/sink.csv:ro \
-v <path/to/rules.csv>:/home/rules.csv:ro \
-v <path/to/output_folder>:/home/outdir \
-w /home \
retropath2 python src/RetroPath2.py \
-sinkfile <sink_file> \
-sourcefile <source_file> \
-max_steps 3 \
-rulesfile <rules_file> \
-topx 100 \
-dmin 0 \
-dmax 1000 \
-mwmax_source 1000 \
-mwmax_cof 1000 \
-timeout 30 \
-outdir <outdir_folder> \
-is_forward False
Test
All modes can be tested with:
cd test
./run[-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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