https://github.com/mbhall88/nanovarbench
Evaluating Nanopore-based bacterial variant calling
https://github.com/mbhall88/nanovarbench
bacteria benchmark bioinformatics illumina microbial-genomics nanopore variant-calling
Last synced: 3 months ago
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Evaluating Nanopore-based bacterial variant calling
- Host: GitHub
- URL: https://github.com/mbhall88/nanovarbench
- Owner: mbhall88
- License: mit
- Created: 2023-12-19T01:41:31.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2025-05-07T09:40:34.000Z (5 months ago)
- Last Synced: 2025-07-20T01:40:58.060Z (3 months ago)
- Topics: bacteria, benchmark, bioinformatics, illumina, microbial-genomics, nanopore, variant-calling
- Language: Python
- Homepage: https://doi.org/10.1101/2024.03.15.585313
- Size: 37.4 MB
- Stars: 19
- Watchers: 4
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# NanoVarBench
## Evaluating Nanopore-based bacterial variant calling
This repository holds the code for [our paper][doi] which performs comprehensive benchmarking of SNP and indel variant calling accuracy across 14 diverse bacterial species using Oxford Nanopore Technologies (ONT) and Illumina sequencing.
You can find the results in that paper. Future updates after publication based on new tools, versions, experiments etc. will be reported and shown here.
- [Citation](#citation)
- [Data](#data)
- [Usage](#usage)
## Citation
> Benchmarking reveals superiority of deep learning variant callers on bacterial nanopore sequence data
Michael B. Hall, Ryan R. Wick, Louise M. Judd, An N. T. Nguyen, Eike J. Steinig, Ouli Xie, Mark R. Davies, Torsten Seemann, Timothy P. Stinear, Lachlan J. M. Coin
_eLife_ (2024) 13:RP98300; doi: [10.7554/eLife.98300][doi]
```bibtex
@article{hall_benchmarking_2024,
title = {Benchmarking reveals superiority of deep learning variant callers on bacterial nanopore sequence data},
volume = {13},
copyright = {Creative Commons Attribution-ShareAlike 4.0 International License (CC-BY-SA)},
issn = {2050-084X},
url = {https://doi.org/10.7554/eLife.98300},
doi = {10.7554/eLife.98300},
urldate = {2024-10-17},
journal = {eLife},
author = {Hall, Michael B and Wick, Ryan R and Judd, Louise M and Nguyen, An N and Steinig, Eike J and Xie, Ouli and Davies, Mark and Seemann, Torsten and Stinear, Timothy P and Coin, Lachlan},
editor = {Weigel, Detlef},
month = oct,
year = {2024},
pages = {RP98300},
}
```
## Data
Accessions and DOIs for all data can be found in [`config/accessions.csv`](./config/accessions.csv).
The variant truthsets and associated data for making these is [archived on Zenodo][truth].
## Usage
See [the config docs](./config/README.md) for instructions on how to configure this pipeline for your data.
You will need the following packages to run the pipeline:
- `snakemake`
- `pandas`
- `apptainer` or `singularity`
- `conda`
A script for submitting the master Snakemake job on a Slurm cluster can be found at [`scripts/submit_slurm.sh`](./scripts/submit_slurm.sh).
[doi]: https://doi.org/10.7554/eLife.98300
[truth]: https://zenodo.org/doi/10.5281/zenodo.10867170