| name | cami |
| description | CAMI / CAMI II metagenome benchmarking datasets and evaluation stack (CAMISIM, AMBER, OPAL, CAMI Benchmarking Portal). Use when: (1) Downloading CAMI challenge data / gold standards, (2) Choosing marine, plant-associated, strain-madness, mouse-gut, or human toy sets, (3) Evaluating binners with AMBER or profilers with OPAL, (4) Simulating communities with CAMISIM, (5) Citing CAMI results in Methods without over-generalizing to new biomes. Portal: https://cami-challenge.org/ and https://data.cami-challenge.org/. For real-world public reads use sra-ena; for biome MAG catalogues use mgnify.
|
| license | MIT |
| category | utilities |
| tags | ["CAMI","CAMI2","benchmark","AMBER","OPAL","CAMISIM","gold-standard"] |
| upstream | https://cami-challenge.org/ |
CAMI (Critical Assessment of Metagenome Interpretation)
Portal: https://cami-challenge.org/ ·
Data: https://data.cami-challenge.org/ ·
GitHub org: CAMI-challenge ·
Benchmarking portal paper / server: see References
Citation
Sczyrba, A. et al. Critical Assessment of Metagenome Interpretation—a benchmark
of metagenomics software. Nat. Methods 14, 1063–1071 (2017).
https://doi.org/10.1038/nmeth.4458
Meyer, F. et al. Critical Assessment of Metagenome Interpretation: the second
round of challenges. Nat. Methods 19, 429–440 (2022).
https://doi.org/10.1038/s41592-022-01431-4
Fritz, A. et al. CAMISIM: simulating metagenomes and microbial communities.
Microbiome 7, 17 (2019). https://doi.org/10.1186/s40168-019-0633-6
Meyer, F. et al. AMBER: Assessment of Metagenome BinnERs. GigaScience 7,
giy069 (2018). https://doi.org/10.1093/gigascience/giy069
Meyer, F. et al. Assessing taxonomic metagenome profilers with OPAL.
Genome Biol. 20, 51 (2019). https://doi.org/10.1186/s13059-019-1646-y
Meyer, F. et al. CAMI Benchmarking Portal: online evaluation and ranking of
metagenomic software. Nucleic Acids Res. 53, W102–W109 (2025).
https://doi.org/10.1093/nar/gkaf369
See also docs/references.md and
docs/public-databases.md.
Analytical thinking
CAMI is a community benchmarking initiative, not a natural biome catalogue.
Datasets are computationally constructed (often via CAMISIM) with gold
standards for assembly, genome binning, taxonomic binning, and profiling.
Use CAMI when you need:
| Goal | Resource |
|---|
| Compare assemblers / binners / profilers under controlled truth | CAMI / CAMI II challenge data |
| Generate custom gold-standard simulations | CAMISIM |
| Lightweight Illumina read simulation | insilicoseq |
| Score genome bins vs gold | AMBER |
| Score taxonomic profiles vs gold | OPAL |
| Submit / browse rankings | CAMI Benchmarking Portal |
Do not treat CAMI rankings as a universal ordering for your soil/gut/reactor
study — CAMI II still found related strains hard for assembly/binning, and
viruses/Archaea underperformed for many profilers/binners. Cite the dataset
name (e.g. plant-associated, strain-madness, marine, mouse gut) you actually ran.
Abundance caveat (Sun et al., Nat. Methods 2021): profilers report
sequence abundance vs taxonomic abundance — do not mix them when
scoring with OPAL or comparing MetaPhlAn vs Kraken.
Dataset layers
CAMISIM / community design
↓
short- and/or long-read metagenomes (+ multi-sample designs)
↓
gold standards (assembly / genome binning / tax. binning / profiling)
↓
your tool outputs (bioboxes / CAMI formats)
↓
AMBER (bins) · OPAL (profiles) · portal rankings
CAMI II scale (paper): ~1,700 genomes + ~600 plasmids/viruses; short + long
reads; thousands of submitted results across dozens of program versions.
How to obtain data
Prefer the live portal paths over inventing FTP URLs:
https://cami-challenge.org/
https://data.cami-challenge.org/participate
CAMI II challenge / exemplary datasets were also deposited with PUBLISSO DOIs
(marine, strain-madness, plant-associated, mouse gut, human) — resolve from the
CAMI II paper Data availability / portal, then pin the DOI + download date.
mkdir -p db/cami/<dataset_id>
Evaluation tools
Use CAMI bioboxes / profiling formats when possible so AMBER/OPAL/portal
can ingest outputs without custom parsers.
Decision tree
Need public metagenome *data*?
├─ Controlled benchmark with gold standards → cami (this skill)
├─ Simulate custom communities → CAMISIM (this skill)
├─ Real environmental/clinical reads → sra-ena (± mgnify analysed studies)
├─ Biome MAG / protein catalogues → mgnify
└─ Rank-normalized prokaryotic taxonomy release → gtdb
Methods caveats
- Report CAMI challenge round + dataset ID + gold-standard version
- Separate short-read vs long-read vs hybrid results
- Do not equate CAMI “best tool” with production defaults for all biomes
- Keep sequence- vs taxonomic-abundance definitions explicit in profiler benchmarks
- Reference DBs frozen for a challenge (e.g. RefSeq snapshot dates) ≠ today’s GTDB/MGnify
Related skills
insilicoseq · public-databases · sra-ena · mgnify · gtdb · quast · metabat2 ·
basalt · metaphlan · kraken2 · tool-selection · study-design