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# Welcome to sourmash!

sourmash is a command-line tool and Python library for computing
[hash sketches](https://en.wikipedia.org/wiki/MinHash) from DNA
sequences, comparing them to each other, and plotting the results.
This allows you to estimate sequence similarity between even very
large data sets quickly and accurately.

sourmash can be used to quickly search large databases of genomes
for matches to query genomes and metagenomes; see [our list of
available databases](databases.md).

sourmash also includes k-mer based taxonomic exploration and
classification routines for genome and metagenome analysis. These
routines can use the NCBI and GTDB taxonomies but do not depend on them
specifically.

We have [several tutorials](tutorials.md) available! Start with
[Making signatures, comparing, and searching](tutorial-basic.md).

The paper [Large-scale sequence comparisons with sourmash (Pierce et al., 2019)](https://f1000research.com/articles/8-1006)
gives an overview of how sourmash works and what its major use cases are.
Please also see the `mash` [software](http://mash.readthedocs.io/en/latest/) and
[paper (Ondov et al., 2016)](http://dx.doi.org/10.1186/s13059-016-0997-x) for
background information on how and why MinHash works.

**Questions? Thoughts?** Ask us on the [sourmash issue tracker](https://github.com/sourmash-bio/sourmash/issues/)!

**Want to migrate to sourmash v4?** sourmash v4 is now available, and
has a number of incompatibilites with v2 and v3. Please see
[our migration guide](support.md#migrating-from-sourmash-v3x-to-sourmash-v4x)!

----

To use sourmash, you must be comfortable with the UNIX command line;
programmers may find the [Python library and API](api.md) useful as well.

If you use sourmash, please cite us!

> Brown and Irber (2016),
> **sourmash: a library for MinHash sketching of DNA**.
> Journal of Open Source Software, 1(5), 27, [doi:10.21105/joss.00027](https://joss.theoj.org/papers/3d793c6e7db683bee7c03377a4a7f3c9)
## sourmash in brief

sourmash uses MinHash-style sketching to create "signatures", compressed
representations of DNA/RNA sequence. These signatures can then
be stored, searched, explored, and taxonomically annotated.

* `sourmash` provides command line utilities for creating, comparing,
and searching signatures, as well as plotting and clustering
signatures by similarity (see [the command-line docs](command-line.md)).

* `sourmash` can **search very large collections of signatures** to find matches
to a query.

* `sourmash` can also **identify parts of metagenomes that match known genomes**,
and can **taxonomically classify genomes and metagenomes** against databases
of known species.
```{contents} Contents
:depth: 3
```

* `sourmash` can be used to **search databases of public sequences**
(e.g. all of GenBank) and can also be used to create and search databases
of **private sequencing data**.
sourmash is a command-line tool and Python/Rust library for
**metagenome analysis** and **genome comparison** with k-mers. It
supports the compositional analysis of metagenomes, rapid search of
large sequence databases, and flexible taxonomic analysis with both
NCBI and GTDB taxonomies. sourmash works well with sequences 30kb or
larger, including bacterial and viral genomes.

* `sourmash` supports saving, loading, and communication of signatures
via [JSON](http://www.json.org/), a ~human-readable and editable format.
You might try sourmash if you want to -

* `sourmash` also has a simple Python API for interacting with signatures,
including support for online updating and querying of signatures
(see [the API docs](api.md)).
* identify which reference genomes to map your metagenomic reads to
* search all Genbank microbial genomes with a sequence query
* cluster many genomes by similarity
* taxonomically classify genomes or metagenomes against NCBI and/or GTDB;
* search thousands of metagenomes with a query genome or sequence

* `sourmash` relies on an underlying Rust core for performance.
Our **vision**: sourmash strives to support biologists in analyzing
modern sequencing data at high resolution and with full context,
including all public reference genomes and metagenomes.

* `sourmash` is developed [on GitHub](https://github.com/sourmash-bio/sourmash)
and is **freely and openly available** under the BSD 3-clause license.
Please see [the README](https://github.com/sourmash-bio/sourmash/blob/latest/README.md)
for more information on development, support, and contributing.
## How does sourmash work?

You can take a look at sourmash analyses on real data
[in a saved Jupyter notebook](https://github.com/sourmash-bio/sourmash/blob/latest/doc/sourmash-examples.ipynb),
and experiment with it yourself
[interactively in a Jupyter Notebook](https://mybinder.org/v2/gh/sourmash-bio/sourmash/latest?labpath=doc%2Fsourmash-examples.ipynb)
at [mybinder.org](http://mybinder.org).
Underneath, sourmash uses [FracMinHash sketches](https://www.biorxiv.org/content/10.1101/2022.01.11.475838) for fast and
lightweight sequence comparison; FracMinHash builds on
[MinHash sketching](https://en.wikipedia.org/wiki/MinHash) to support both Jaccard similarity
_and_ containment analyses with k-mers. This significantly expands
the range of operations that can be done quickly and in low
memory. sourmash also implements a number of new and powerful analysis
techniques, including minimum metagenome covers and alignment-free ANI
estimation.

## Installing sourmash
sourmash is inspired by [mash](https://mash.readthedocs.io), and
supports most mash analyses. sourmash also implements an expanded set
of functionality for metagenome and taxonomic analysis.

You can use pip:
```bash
$ pip install sourmash
```
sourmash development was initiated with a grant from the Moore
Foundation under the Data Driven Discovery program, and has been
supported by further funding from the NIH and NSF. Please see
[funding acknowledgements](funding.md) for details!

or conda:
```bash
$ conda install -c conda-forge -c bioconda sourmash
```
## Mission statement

Please see [the README file in github.com/sourmash-bio/sourmash](https://github.com/sourmash-bio/sourmash/blob/latest/README.md)
for more information.
The project mission is to provide practical tools and approaches for
analyzing extremely large sequencing data sets, with an emphasis on
high resolution results. We design around the following principles:

## Memory and speed
* genomic and metagenomic analyses should be able to make use of all
available reference genomes.
* metagenomic analyses should support assembly independent approaches,
to avoid biases stemming from low coverage or high strain
variability.
* private and public databases should be equally well supported.
* a variety of data structures and algorithms are necessary to support
a wide set of use cases, including efficient command-line analysis,
real-time queries, and massive-scale batch analyses.
* our tools should be well behaved members of the bioinformatics
analysis tool ecosystem, and use common installation approaches,
standard formats, and semantic versioning.
* our tools should be robustly tested, well documented, and supported.
* we discuss scientific and computational tradeoffs and make specific
recommendations where possible, admitting uncertainty as needed.

sourmash has relatively small disk and memory requirements compared to
many other software programs used for genome search and taxonomic
classification.
## Using sourmash

`sourmash search` and `sourmash gather` can be used to search 100k
genbank microbial genomes ([using our prepared databases](databases.md))
with about 20 GB of disk and in under 1 GB of RAM.
Typically a search for a single genome takes about 30 seconds on a laptop.
### Tutorials and examples

`sourmash lca` can be used to search/classify against all genbank
microbial genomes with about 200 MB of disk space and about 10 GB of
RAM. Typically a metagenome classification takes about 1 minute on a
laptop.
These tutorials are command line tutorials that should work on Mac OS
X and Linux. They require about 5 GB of disk space and 5 GB of RAM.

## sourmash versioning
* [The first sourmash tutorial - making signatures, comparing, and searching](tutorial-basic.md)

We support the use of sourmash in pipelines and applications
by communicating clearly about bug fixes, feature additions, and feature
changes. We use version numbers as follows:
* [Using sourmash LCA to do taxonomic classification](tutorials-lca.md)

* Major releases, like v4.0.0, may break backwards compatibility at
the command line as well as top-level Python/Rust APIs.
* Minor releases, like v4.1.0, will remain backwards compatible but
may introduce significant new features.
* Patch releases, like v4.1.1, are for minor bug fixes; full backwards
compatibility is retained.
* [Analyzing the genomic and taxonomic composition of an environmental genome using GTDB and sample-specific MAGs with sourmash](tutorial-lemonade.md)

If you are relying on sourmash in a pipeline or application, we
suggest specifying your version requirements at the major release,
e.g. in conda you would specify `sourmash>=3,<4`.
* [Some sourmash command line examples!](sourmash-examples.ipynb)

See [the Versioning docs](support.md) for more information on what our
versioning policy means in detail, and how to migrate between major
versions!
### How-To Guides

## Limitations
* Installing sourmash

**sourmash cannot find matches across large evolutionary distances.**
* [Classifying genome sketches](classifying-signatures.md)

sourmash seems to work well to search and compare data sets for
nucleotide matches at the species and genus level, but does not have much
sensitivity beyond that. (It seems to be particularly good at
strain-level analysis.) You should use protein-based analyses
to do searches across larger evolutionary distances.
* [Working with private collections of genome sketches.](sourmash-collections.ipynb)

**sourmash signatures can be very large.**
* [Using the `LCA_Database` API.](using-LCA-database-API.ipynb)

We use a modification of the MinHash sketch approach that allows us
to search the contents of metagenomes and large genomes with no loss
of sensitivity, but there is a tradeoff: there is no guaranteed limit
to signature size when using 'scaled' signatures.
* [Building plots from `sourmash compare` output](plotting-compare.ipynb).

## Logo
* [A short guide to using sourmash output with R](other-languages.md).

The sourmash logo was designed by Stéfanie Fares Sabbag,
with feedback from Clara Barcelos,
Taylor Reiter and Luiz Irber.
### How sourmash works under the hood

<a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/"><img
alt="Creative Commons License" style="border-width:0"
src="https://i.creativecommons.org/l/by-sa/4.0/88x31.png" /></a><br />
* [An introduction to k-mers for genome comparison and analysis](kmers-and-minhash.ipynb)
* [Support, versioning, and migration between versions](support.md)

The logo
is licensed under a <a rel="license"
href="http://creativecommons.org/licenses/by-sa/4.0/">Creative Commons
Attribution-ShareAlike 4.0 International License</a>.
### Reference material

## Contents:
* [UNIX command-line documentation](command-line.md)
* [Genbank and GTDB databases and taxonomy files](databases.md)
* [Python examples using the API](api-example.md)
* [Publications about sourmash](publications.md)
* [A guide to the internals of sourmash](sourmash-internals.md)
* [Funding acknowledgements](funding.md)

```{toctree}
---
maxdepth: 2
---
command-line
tutorials
using-sourmash-a-guide
classifying-signatures
databases
api
more-info
support
developer
```
## Developing and extending sourmash

# Indices and tables
* [Releasing a new version of sourmash](release.md)

* {ref}`genindex`
* {ref}`modindex`
* {ref}`search`
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