sketchlib 0.4.1

Genome and amino-acid sketching
Documentation

sketchlib.rust

Cargo Build & Test Clippy check docs.rs codecov Crates.io GitHub release (latest SemVer)

Description

This is a reimplementation and extension of pp-sketchlib in the rust language. This version is optimised for larger sample numbers, particularly allowing subsets of samples to be compared.

News

  • Data format changed in v0.4.0. If you have an older database (see sketchlib info <db_prefix> | grep "sketch_version") you should resketch samples with >v0.4 if possible. Otherwise you will need to use an older release available on crates.io.
  • v0.2.0 was the first stable release.

Documentation

See https://docs.rs/sketchlib

Installation

Choose from:

  1. Download a binary from the releases.
  2. Use cargo install sketchlib or cargo add sketchlib.
  3. Use conda install -c bioconda sketchlib.
  4. Build from source

For 2) or 4) you must have the rust toolchain installed.

OS X users

If you have an M1-4 (arm64) Mac, we aren't currently automatically building binaries, so would recommend either option 2) or 3) for best performance.

If you get a message saying the binary isn't signed by Apple and can't be run, use the following command to bypass this:

xattr -d "com.apple.quarantine" ./sketchlib

Build from source

  1. Clone the repository with git clone.
  2. Run cargo install --path . or RUSTFLAGS="-C target-cpu=native" cargo install --path . to optimise for your machine.

Citation

Please cite:

von Wachsmann J, Lorenz LJ, Russell MJ, Gurbich TA, Rodríguez-Bouza V, Horsfield ST, Lees JA, Finn RD (2026).
Rapid and consistent clustering of millions of genomes highlights the diversity of prokaryotic life.
bioRxiv.

https://doi.org/10.64898/2025.12.30.695181

Lees JA, Tonkin-Hill G, Yang Z, Corander J.
Mandrake: visualizing microbial population structure by embedding millions of genomes into a low-dimensional representation.
Philosophical Transactions of The Royal Society B. 2022;377: 20210237.

https://doi.org/10.1098/rstb.2021.0237

We rely on algorithms from:

bindash (written by XiaoFei Zhao):
Zhao, X. BinDash, software for fast genome distance estimation on a typical personal laptop.
Bioinformatics 35:671–673 (2019).
doi:10.1093/bioinformatics/bty651

ntHash (written by Hamid Mohamadi):
Mohamadi, H., Chu, J., Vandervalk, B. P. & Birol, I. ntHash: recursive nucleotide hashing.
Bioinformatics 32:3492–3494 (2016).
doi:10.1093/bioinformatics/btw397