SNPio: A Python API for Population Genomic Data I/O, Filtering, Analysis, and Encoding
SNPio is a Python package designed to streamline the process of reading, filtering, encoding, and analyzing genotype alignments. It supports VCF, PHYLIP, STRUCTURE, and GENEPOP file formats, and provides high-level tools for visualization, downstream machine learning analysis, and population genetic inference.
SNPio Includes:
- File I/O (VCFReader, PhylipReader, StructureReader, GenePopReader)
- Genotype filtering (NRemover2)
- Genotype encoding for AI & machine learning applications (GenotypeEncoder)
- Population genetic statistics & Principal Component Analysis (PopGenStatistics)
- Finite-sample-unbiased unphased LD and LD-based recent effective population size (Ne), with grouped-locus bootstrap intervals and validation evidence
- Patterson, partitioned, and DFOIL statistics with random, deterministic least-missing, all-sample, or explicit individual selection
- Artifact-aware output organization and interactive MultiQC reporting
- Experimental: Phylogenetic tree parsing (TreeParser)
📖 Full Documentation
Detailed API usage, tutorials, and examples are available in the Documentation
🔧 Installation
You can install SNPio using one of the following methods:
✅ Pip Installation
python3 -m venv snpio-env
source snpio-env/bin/activate
pip install snpio
✅ Conda Installation
conda create -n snpio-env python=3.12
conda activate snpio-env
conda install -c btmartin721 snpio
🐳 Docker
To run the Docker image interactively in a terminal, run the following commands:
docker pull btmartin721/snpio:latest
docker run -it btmartin721/snpio:latest
If you'd like to run SNPio in a jupyter notebook, instructions to do so in the docker container will be printed to the terminal.
Note: All three installation versions (pip, conda, docker) are actively maintained and kept up-to-date with CI/CD routines.
Note: SNPio supports Unix-based systems. Windows users should install via WSL.
🚀 Getting Started
Import Modules
from snpio import (
NRemover2, VCFReader, PhylipReader, StructureReader,
GenePopReader, GenotypeEncoder, PopGenStatistics
)
Load Genotype Data (VCF Example)
vcf = "snpio/example_data/vcf_files/phylogen_subset14K_sorted.vcf.gz"
popmap = "snpio/example_data/popmaps/phylogen_nomx.popmap"
gd = VCFReader(
filename=vcf,
popmapfile=popmap,
force_popmap=True,
verbose=True,
plot_format="png",
prefix="snpio_example"
)
You can also specify include_pops and exclude_pops to control population-level filtering.
LD and Recent Effective Population Size
from snpio import PopGenStatistics
ld = PopGenStatistics(gd).calculate_linkage_disequilibrium(
n_bootstraps=200,
n_jobs=-1,
max_pairs=1_000_000,
seed=42,
)
print(ld.summary[["Population", "r2D", "rDz", "Ne"]])
The returned scientific table represents non-estimable Ne values as NaN.
The MultiQC population summary adds a human-readable Ne_Status column.
For ordinary VCF input, SNPio infers chromosome or scaffold groups and uses
only between-group locus pairs. Coordinate-free data must provide explicit
locus_groups or deliberately set assume_unlinked=True. See the
LD method guide
and validation protocol.
Output Layout
SNPio separates generated data, logs, MultiQC bundles, plots, and tabular
reports under <prefix>_output/. Results derived from an NRemover2 object
are placed under plots/nremover/<operation>/ and
reports/nremover/<operation>/; VCF metadata caches use data/vcf/ with
independent filtered states under data/vcf/nremover/.
🧪 Development Notes
To run the unit tests:
python -m pip install -e '.[dev]'
python -m pytest tests/
The optional forward-time LD calibration dependencies are isolated from the runtime installation:
python -m pip install -e '.[dev,ld-validation]'
🧾 License and Citation
SNPio is licensed under the GPL-3.0 License.
Please cite:
Martin, B. T., Monaco, D. R., Sharabi, N., Mussmann, S. M., and Chafin, T. K. (2026). SNPio: a Python interface for population genomic data processing. BMC Bioinformatics. https://doi.org/10.1186/s12859-026-06546-5
When reporting unphased LD or LD-based recent Ne, also cite Ragsdale and Gravel (2020), Molecular Biology and Evolution, 37(3), 923–932.
🤝 Contributing
We welcome community contributions!
- Report bugs or request features on GitHub Issues
- Submit a pull request
- See CONTRIBUTING.md for contributing guidelines.
🙏 Acknowledgments
Thanks for using SNPio. We hope it facilitates your population genomic research. Feel free to reach out with questions or feedback!
1 maintainer
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