| name | petasearch |
| description | Petasearch — efficient parallelized peta-scale protein database search (Steinegger lab). Use when: (1) Searching enormous protein collections beyond routine MMseqs2 setups, (2) Preindexing large target lists for repeated queries, (3) Selective Smith–Waterman after coarse filters. Upstream: https://github.com/steineggerlab/petasearch. Route via homology-search; compare mmseqs2 / erast.
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| license | MIT |
| category | analysis-tools |
| tags | ["Petasearch","protein-search","peta-scale","homology"] |
| upstream | https://github.com/steineggerlab/petasearch |
| stage | function |
Petasearch
Upstream: steineggerlab/petasearch
Citation
See upstream README / releases for the current preferred citation; software at
https://github.com/steineggerlab/petasearch. Cross-link Steinegger-lab search
stack in docs/references.md.
Analytical thinking
Petasearch targets very large protein target sets with create-DB /
preindex / easy workflows and optional selective SW alignment
(block-aligner). Use when warehouse-scale protein search is the bottleneck;
for standard MAG catalogues prefer mmseqs2, for embedding retrieval erast.
Requires Rust toolchain to build from source — follow upstream install notes.
Verify exact binary names/easy-petasearch flags against the installed tag
(README examples evolve).
How to run
Decision tree
Protein search scale?
├─ Routine / NR catalogues → mmseqs2
├─ Peta-scale / custom huge targets → petasearch
├─ Vector embeddings → erast
└─ Structure → foldseek
Related skills
homology-search · mmseqs2 · erast · foldseek · lexicmap ·
tool-selection
