| name | gapseq |
| description | Predict bacterial metabolic pathways and reconstruct genome-scale metabolic models. Use this skill when working with gapseq: installing, choosing parameters, running commands, interpreting outputs, or troubleshooting. Upstream: https://github.com/jotech/gapseq. For routing across mining tasks use microbial-mining. For stage order use metagenomics-workflow.
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| license | MIT |
| category | analysis-tools |
| tags | ["metabolism","GEMs","genome-mining"] |
| upstream | https://github.com/jotech/gapseq |
| stage | mining |
gapseq
Upstream: gapseq
Citation
Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. Genome Biol. 22, 81 (2021). https://doi.org/10.1186/s13059-021-02295-1
See also docs/references.md.
Analytical thinking
Downstream of genome annotation for pathway/model mining. Needs reasonably complete MAGs; low-completeness bins produce hollow models. Interpret human/gut context with vmh when relevant.
How to run
conda install -c bioconda gapseq
gapseq find -p all genome.fa
gapseq draft -r genome -c genome-draft.RDS -p genome-all-Reactions.tbl -b 136
gapseq fill -m genome-draft.RDS -n genome-Medium.csv -c genome-rxnWeights.RDS -n genome-rxnXgenes.RDS
Key parameters
| completeness | prefer high-quality MAGs | |
| pathways | -p all costly | |
Decision notes
- Run mining on QC-filtered genomes/MAGs (or contigs for MGE/virus screens)
- Computational hits are hypotheses — state validation limits in Methods
- Pin software + database releases
Related skills
dram · bakta · checkm2 · eggnog-mapper · microbial-mining · tool-selection · metagenomics-workflow
vmh
