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tools for comparing biological sequences with k-mer sketches

Project description


Quickly search, compare, and analyze genomic and metagenomic data sets.

Project Status: Active – The project has reached a stable, usable state and is being actively developed. License: 3-Clause BSD Documentation Gitter

DOI pyOpenSci

Bioconda install PyPI Conda Platforms

Python 3.10 Python 3.11 Python 3.12 Build Status codecov


sourmash sketch dna *.fq.gz
sourmash compare *.sig -o distances.cmp -k 31
sourmash plot distances.cmp

sourmash 1.0 is published on JOSS; please cite that paper if you use sourmash (doi: 10.21105/joss.00027):.

The latest major release is sourmash v4, which has several command-line and Python incompatibilities with previous versions. Please visit our migration guide to upgrade!

sourmash is a k-mer analysis multitool, and we aim to provide stable, robust programmatic and command-line APIs for a variety of sequence comparisons. Some of our special sauce includes:

  • FracMinHash sketching, which enables accurate comparisons (including ANI) between data sets of different sizes
  • sourmash gather, a combinatorial k-mer approach for more accurate metagenomic profiling

Please see the sourmash publications for details.

The name is a riff off of Mash, combined with @ctb's love of whiskey. (Sour mash is used in making whiskey.)

Maintainers: C. Titus Brown (@ctb), Luiz C. Irber, Jr (@luizirber), and N. Tessa Pierce-Ward (@bluegenes).

sourmash was initially developed by the Lab for Data-Intensive Biology at the UC Davis School of Veterinary Medicine, and now includes contributions from the global research and developer community.


We recommend using conda-forge to install sourmash:

conda install -c conda-forge sourmash-minimal

This will install the latest stable version of sourmash 4.

You can also use pip to install sourmash:

pip install sourmash

A quickstart tutorial is available.


sourmash runs under Python 3.10 and later on Windows, Mac OS X, and Linux. The base requirements are screed, cffi, numpy, matplotlib, and scipy. Conda will install everything necessary, and is our recommended installation method (see below).

Installation with conda

conda-forge is a community maintained channel for the conda package manager. installing conda, you can install sourmash by running:

$ conda create -n sourmash_env -c conda-forge sourmash-minimal
$ conda activate sourmash_env
$ sourmash --help

which will install the latest released version.


For questions, please open an issue on Github, or ask in our chat.


Development happens on github at sourmash-bio/sourmash.

sourmash is developed in Python and Rust, and you will need a Rust environment to build it; see the developer notes for our suggested development setup.

After installation, sourmash is the main command-line entry point; run it with python -m sourmash, or do pip install -e /path/to/repo to do a developer install in a virtual environment.

The sourmash/ directory contains the Python library and command-line interface code.

The src/core/ directory contains the Rust library implementing core functionality.

Tests require py.test and can be run with make test.

Please see the developer notes for more information on getting set up with a development environment.

CTB Jan 2024

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