Seqwin: Ultrafast identification of signature sequences in microbial genomes
Project description
Seqwin
Seqwin is a lightning‑fast, memory‑efficient toolkit for discovering signature sequences (genomic markers) that balance high sensitivity with high specificity. It builds a minimizer‑based pan‑genome graph across target and neighboring non‑target genomes and extracts signature sequences using a novel graph algorithm. Signatures can be used for downstream assay design such as qPCR, ddPCR, amplicon sequencing and hybrid capture probes.
Seqwin computes minimizers with ntHash, using code adopted from btllib (licensed under the GNU General Public License v3.0).
Table of contents
See the Seqwin Wiki for full documentation.
Installation
Seqwin can be installed from Bioconda or PyPI.
- Bioconda is the recommended installation method because it can install Seqwin and all its dependencies. But it requires Conda and supports Linux and macOS only.
- PyPI (
pip install seqwin) supports Windows (x64), Linux, and macOS, but installs only Seqwin and its Python dependencies. Non-Python dependencies can be installed separately (optional for core Seqwin features).
Bioconda (recommended)
Works on Linux (x64 / arm64) and macOS (Intel / Apple Silicon).
If Conda is not installed, install it with miniforge or miniconda.
1. Create a new Conda environment "seqwin" and install Seqwin via Bioconda
conda create -n seqwin seqwin \
--channel conda-forge \
--channel bioconda \
--strict-channel-priority
2. Activate the environment and verify the install
conda activate seqwin
seqwin --help
PyPI
Works on Windows (x64), Linux (x64 / arm64), and macOS (Intel / Apple Silicon).
1. Install Seqwin from PyPI
python -m pip install --upgrade pip
python -m pip install seqwin
seqwin --help
2. Install non-Python dependencies (optional)
Seqwin can run without these tools, but some features will be unavailable or skipped. See the Command Line Parameters for details.
- Mash (see the publication)
- NCBI BLAST+
- NCBI Datasets CLI
Quick start
Identify signatures by providing one or more target taxa and non-target neighboring taxa.
seqwin \
-t "Salmonella enterica subsp. diarizonae" \
-n "Salmonella enterica subsp. salamae" \
-n "Salmonella bongori" \
--threads 8
Taxa names must be exact matches to NCBI Taxonomy.
Outputs are written to seqwin-out/ in your working directory (see Description of Outputs).
Alternatively, a list of target or non-target genomes can be provided as a text file of file paths. Each line should be the path to a genome FASTA file (plain text or gzipped).
seqwin --tar-paths targets.txt --neg-paths non-targets.txt
Below is an example of targets.txt or non-targets.txt
./genomes/GCA_003718275.1_ASM371827v1_genomic.fna
/data/genomes/GCA_000389055.1_46.E.09_genomic.fna
/data/genomes/GCA_008363955.1_ASM836395v1_genomic.fna.gz
Expected runtime (with --threads 8 or -p 8):
- ~5min and 2.5GB peak RAM for ~500 bacterial genomes with default settings.
- ~5min and 23GB peak RAM for ~15k bacterial genomes with
--no-blastand--no-mash.
Run seqwin --help or seqwin -h to see the full command line interface.
Citation
If you use Seqwin in your research, please cite:
Michael X. Wang, Bryce Kille, Michael G. Nute, Siyi Zhou, Lauren B. Stadler, and Todd J. Treangen "Seqwin: Ultrafast identification of signature sequences in microbial genomes". Proceedings of ISMB 2026, accepted (2026).
Benchmarking datasets, outputs and scripts are available on Zenodo.
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Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@0ead8ec3f3e4b4292f3f311d0dfa6e95fdffdb5e -
Trigger Event:
push
-
Statement type: