refineGEMs 1.2.0

refineGEMs: a python package intended to help with the curation of genome-scale metabolic models (GEMS)

refineGEMs

refineGEMs is a python package inteded to help with the curation of genome-scale metabolic models (GEMS).

Documentation

The docs can be found here.

Overview

Currently refineGEMs can be used for the investigation of a GEM, it can complete the following tasks:

• loading GEMS with cobrapy and libSBML
• report number of metabolites, reactions and genes
• report orphaned, deadends and disconnected metabolites
• report mass and charge unbalanced reactions
• report Memote score
• compare the genes present in the model to the genes found in the KEGG Database (Note: this requires a gff file of your organism and the KEGG identifier of your organism)
• compare the charges and masses of the metabolites present in the model to the charges and masses denoted in the ModelSEED Database

Other applications of refineGEMs include curation of a given model these include:

• correction of a model created with CarveMe v.1.5.1 (for example moving all relevant information from the notes to the annotation field) this includes automated annotation of NCBI genes to the GeneProtein section of the model
• addition of KEGG Pathways as Groups (using the libSBML Groups Plugin)
• SBO-Term annotation based on a script by Elisabeth Fritze
• annotation of metabolites based using a table created by the user data/manual_annotations.xlsx

Installation

You can install refineGEMs via pip:

pip install refinegems

or to a local conda environment where refineGEMs is distributed via this github repository and all dependencies are denoted in the setup.py file:

# clone or pull the latest source code
git clone https://github.com/draeger-lab/refinegems.git
cd refinegems

conda create -n <EnvName> python=3.9

conda activate <EnvName>

# check that pip comes from <EnvName>
which pip

pip install .