| name | phylign |
| description | Phylign — BLAST-like alignment of genes, plasmids, or reads against phylogeny-compressed microbial genome collections (e.g. pre-2019 661k bacteria) on ordinary desktops. Uses phylogenetic compression (MiniPhy for building compressed assemblies/COBS indexes; Phylign for search via COBS + Minimap2). Use when searching huge genome warehouses without a cluster. Upstream: https://github.com/karel-brinda/phylign. Project: https://brinda.eu/mof. Route via homology-search; compare lexicmap.
|
| license | MIT |
| category | analysis-tools |
| tags | ["Phylign","MiniPhy","phylogenetic-compression","search","COBS","genomes"] |
| upstream | https://github.com/karel-brinda/phylign |
| stage | mapping |
Phylign (phylogenetic compression search)
Upstream: karel-brinda/phylign ·
Compression builder: karel-brinda/miniphy ·
https://brinda.eu/mof
Citation
Břinda, K. et al. Efficient and robust search of microbial genomes via
phylogenetic compression. Nat. Methods 22, 692–697 (2025).
https://doi.org/10.1038/s41592-025-02625-2
See also docs/references.md.
Analytical thinking
Public microbial collections outgrow BLAST-style local search. Phylogenetic
compression reorders genomes by estimated evolutionary history so XZ / COBS /
Minimap2 work on highly compressible batches.
| Component | Role |
|---|
| MiniPhy | Build phylogeny-compressed assemblies / indexes from genome batches |
| Phylign | Query compressed 661k-style DBs: COBS match → Minimap2 align |
| vs | Prefer Phylign when |
|---|
lexicmap | Using phylogeny-compressed 661k / MOF collections on a laptop |
mmseqs2 | Nucleotide genome warehouse search (not protein catalogue) |
minimap2 alone | Target set is millions of assemblies (needs compression/index stack) |
Requirements (upstream): ~12 GB RAM, ~120 GB disk for DB + intermediates.
Pin which compressed collection you downloaded.
How to run
git clone https://github.com/karel-brinda/phylign.git
cd phylign
make test
make download
make
Building new compressed libraries: use MiniPhy
(https://github.com/karel-brinda/miniphy), then search with Phylign-style
workflows.
Decision tree
Search vs huge bacterial genome collections?
├─ Phylogeny-compressed 661k / MOF on desktop → phylign
├─ Custom million-genome nucleotide index → lexicmap
├─ Protein homology → mmseqs2 / erast / foldseek
└─ Short reads → contigs for binning → strobealign / bowtie2
Related skills
homology-search · lexicmap · minimap2 · progenomes · gtdb ·
tool-selection
