mergem is a Python library for merging two or more genome-scale metabolic models. The library is publicly available via PyPI at https://pypi.org/project/mergem/ and can be pip installed. mergem can be used on the command-line and can also be imported within python scripts. The package can take models in various COBRApy compatible formats such as SBML, JSON, etc. and even COBRApy model objects, when the package is imported. The results of a single merge include the merged model, jaccard distances between all pairs of models, number of metabolites and reactions merged, and lists of models that contain each metabolite and reaction.
For each input model, mergem converts the metabolite IDs into a common namespace using a database ID mapping dictionary. Reactions are compared using the participating metabolites (after conversion to common namespace). The metabolite ID mapping dictionary contains metabolite identifiers from various databases such as ModelSEED, KEGG, ChEBI, and MetaNetX that have been unified per metabolite. The dictionary thus allows for model metabolites to be compared more efficiently. The mapping dictionaries can be updated, during which the latest identifier information is downloaded from each database and identifiers representing the same metabolite are mapped to one another.
mergem is also available in the user-friendly application Fluxer, which produces tidy flux graphs that can visually compare the complete metabolic network from multiple models. Documentation for Fluxer based merging can be found on its tutorial page
- Installing the mergem package
- Using mergem to merge models
- Understanding mergem results
- Visually comparing genome-scale metabolic models
- Updating Database ID mapping dictionaries
- Save ID mapping tables
- Use examples
- Citing mergem
This project is under active development.