ADToolbox
From raw amplicon reads to a calibrated anaerobic digestion model.
ADToolbox is developed in the Chan Lab at Colorado State University. It connects metagenomics evidence, curated reaction and feed databases, and dynamic ADM1 / e-ADM simulations into one reproducible Python and command-line workflow.
Anaerobic digestion models such as ADM1 lump the microbial community into a handful of guilds whose initial biomass you are expected to guess. ADToolbox replaces that guess with measurement: it takes 16S amplicon data, maps it through GTDB and a curated enzyme-to-reaction database, and produces the microbial COD allocation the model needs.
📖 Read the documentation
Install
pip install adtoolbox # base install, Python 3.11+
pip install "adtoolbox[optimize]" # + parameter-tuning backends
pip install "adtoolbox[dashboard]" # + interactive Dash/Escher visualization
Or use the container, which bundles fastp, VSEARCH, MMseqs2, and the SRA Toolkit:
docker run --rm parsaghadermazi/adtoolbox:latest adtoolbox --help
See the installation guide for source installs, extras, external tools, and HPC notes.
Quick start
# 1. Download the reference databases
adtoolbox database download-all-databases --output-dir ./database
# 2. Turn amplicon samples into microbial COD allocations
adtoolbox metagenomics process \
--input ./samples.tsv --input-type sra --assay amplicon \
--output-dir ./process --sra-dir ./sra \
--database-dir ./database --execute
# Use the direct functional route for shotgun reads
adtoolbox metagenomics process \
--input ./shotgun_samples.tsv --input-type reads --assay shotgun \
--output-dir ./process --database-dir ./database --execute
# 3. Simulate
adtoolbox adm e-adm --models-json reference_data/models.json --report csv
The full walkthrough is in the Quickstart.
Documentation map
| Page | Contents |
|---|---|
| Quickstart | Install, databases, first simulation, first pipeline run. |
| Metagenomics Pipeline | Sample tables, execution profiles, Slurm, output schemas. |
| ADM Models | Input contracts, stoichiometry, rate laws, inhibition terms. |
| Parameter Tuning | Fitting kinetic parameters to experimental data. |
| CLI | Every command and option. |
| Python API | Generated reference for all modules. |
Try it without installing
The example notebooks run on Binder. Note that Escher map visualization is not available there.
Building the docs locally
pip install -r docs/requirements.txt
mkdocs serve
Contact
Developed in the Chan Lab at Colorado State University.
| Parsa Ghadermazi | parsa.ghadermazi@colostate.edu |
| Ethan Rimelman | rimelman@colostate.edu |
| Siu Hung Joshua Chan (PI) | joshua.chan@colostate.edu |
Metadata
Release files for adtoolbox 1.1.16
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| adtoolbox-1.1.16.tar.gz | 112.6 kB | Without provenance | Details for adtoolbox-1.1.16.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| adtoolbox-1.1.16-py3-none-any.whl | Python 3 | none | any | Details for adtoolbox-1.1.16-py3-none-any.whl |
Total release size: 228.8 kB
Release files / adtoolbox-1.1.16.tar.gz
| Download URL | adtoolbox-1.1.16.tar.gz |
|---|---|
| Size | 112.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
91c17207b4d7ba9dab0af2a077d0b72503e5d8a241ba1dd00a0f908c73e9fecb
|
|
BLAKE2b-256 checksum How to use checksums |
ca0e0db7b5418609c7f88c7fa333ac372ff7d0ef5f3208109ef4273ace57d929
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.1.4 CPython/3.13.7 Darwin/24.5.0
|
Release files / adtoolbox-1.1.16-py3-none-any.whl
| Download URL | adtoolbox-1.1.16-py3-none-any.whl |
|---|---|
| Size | 116.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
ad5d9df879b2be4ed15517232c53fd3b49a3493aef009644539c6b931e5b8696
|
|
BLAKE2b-256 checksum How to use checksums |
ebf9b948b7c78426004e4b55bf0b8b5b42d5c4868bd27474c574f81b6f893c8d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.1.4 CPython/3.13.7 Darwin/24.5.0
|
Security for adtoolbox 1.1.16
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.