| name | binchicken |
| description | Bin Chicken — targeted coassembly planning for recovering low-abundance / novel MAGs by grouping metagenomes that share marker-gene signal (SingleM). Use when: (1) Public or large cohorts where all-vs-all coassembly is impossible, (2) Prioritizing sample subsets for coassembly to recover rare lineages, (3) Novelty-focused recovery against reference genomes, (4) Study-design of coassembly strata. Upstream: https://github.com/AroneyS/binchicken. For general coassembly vs individual design use study-design. For binning after coassembly use basalt / metabat2 / etc.
|
| license | MIT |
| category | analysis-tools |
| tags | ["coassembly","low-abundance","BinChicken","SingleM","MAG"] |
| upstream | https://github.com/AroneyS/binchicken |
| stage | assembly |
Bin Chicken
Upstream: AroneyS/binchicken
Citation
Aroney, S. T. N., Newell, R. J. P., Tyson, G. W. & Woodcroft, B. J. Bin Chicken:
targeted metagenomic coassembly for the efficient recovery of novel genomes.
Nat. Methods (2025). https://doi.org/10.1038/s41592-025-02901-1
See also docs/references.md.
Analytical thinking
Low-abundance genomes are often below recoverable coverage in any single
sample. Blind coassembly of many samples increases graph complexity and
compute; random subsets explode combinatorially.
Bin Chicken plans targeted coassemblies: match SingleM marker sequences
across metagenomes, optionally prioritize markers divergent from references,
then greedily cluster samples into coassembly groups. It is a sample-selection
/ assembly-planning tool — not a replacement for MetaBAT2/BASALT after
contigs exist.
Use when:
- Mining public repositories or large private cohorts for rare/novel lineages
- You need a principled alternative to metadata-only pooling
- You want novelty-weighted recovery (markers distant from known genomes)
Do not use Bin Chicken to justify pooling unrelated biological strata for a
single hypothesis-driven contrast study — see study-design.
Prerequisites
| Requirement | Notes |
|---|
| Inputs | Many metagenomes (reads) + SingleM/Bin Chicken DB stack |
| Compute | Coassembly of selected groups still expensive — plan RAM |
| Downstream | Assemble groups → map → bin (basalt ★ / single binners) → QC |
How to run
Confirm subcommands against upstream (workflow is multi-step):
binchicken \
Then run your assembler (megahit / metaspades) on each planned group and
continue with mapping + binning.
Decision tree
Low-abundance / novelty MAG recovery across many samples?
├─ Need automated coassembly targeting → binchicken
├─ Few related samples, clear strata → study-design + matched co-assembly
├─ After contigs exist → basalt ★ / metawrap / dastool / single binners
└─ Only abundance of known refs → coverm / sylph / metaphlan (not coassembly)
Methods caveats
- Targeted coassembly can still create chimeras — multi-coverage binning and
GUNC/CheckM2 remain mandatory.
- Report marker DB, novelty filter, group size, and assembler.
- Genome counts from large public runs are not transferable to your biome.
Related skills
singlem · study-design · megahit · metaspades · basalt · coverm · gtdbtk ·
tool-selection · metagenomics-workflow
