https://github.com/sanger-tol/variantcalling
Nextflow DSL2 pipeline to call variants on long read alignment.
https://github.com/sanger-tol/variantcalling
alignment genomics nextflow pipeline variant-calling workflow
Last synced: 5 months ago
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Nextflow DSL2 pipeline to call variants on long read alignment.
- Host: GitHub
- URL: https://github.com/sanger-tol/variantcalling
- Owner: sanger-tol
- License: mit
- Created: 2022-04-22T13:54:08.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2025-12-05T15:11:37.000Z (6 months ago)
- Last Synced: 2025-12-05T15:12:54.180Z (6 months ago)
- Topics: alignment, genomics, nextflow, pipeline, variant-calling, workflow
- Language: Nextflow
- Homepage: https://pipelines.tol.sanger.ac.uk/variantcalling
- Size: 4.03 MB
- Stars: 10
- Watchers: 9
- Forks: 9
- Open Issues: 13
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
Awesome Lists containing this project
README
# 
[](https://doi.org/10.5281/zenodo.7890527)
[](https://www.nextflow.io/)
[](https://docs.conda.io/en/latest/)
[](https://www.docker.com/)
[](https://sylabs.io/docs/)
[](https://tower.nf/launch?pipeline=https://github.com/sanger-tol/variantcalling)
## Introduction
**sanger-tol/variantcalling** is a bioinformatics best-practice analysis pipeline for variant calling using [DeepVariant](https://github.com/google/deepvariant) for PacBio data.
The pipeline is built using [Nextflow](https://www.nextflow.io), a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The [Nextflow DSL2](https://www.nextflow.io/docs/latest/dsl2.html) implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. Where possible, these processes have been submitted to and installed from [nf-core/modules](https://github.com/nf-core/modules) in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!
On release, automated continuous integration tests run the pipeline on a full-sized dataset on the LSF infrastructure. This ensures that the pipeline runs on LSF, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources.
## Pipeline summary
The pipeline takes aligned or unaligned PacBio sample reads (CRAM/BAM files) from a CSV file and the reference file in FASTA format, and then uses DeepVariant tool to make variant calling.
Steps involved:
- Split fasta file into smaller files, normally one sequence per file unless the sequences are too small.
- Align the reads if not aligned.
- Merge input BAM/CRAM files together if they have the same sample names.
- Filter out reads using the `-F 0x900` option to only retain the primary alignments.
- Run DeepVariant using filtered BAM/CRAM files against each of split fasta files.
- Merge all VCF and GVCF files generated by DeepVariant by sample together for each input BAM/CRAM file.
- Run VCFtools to calculate heterozygosity and per site nucleotide diversity.
## Quick Start
1. Install [`Nextflow`](https://www.nextflow.io/docs/latest/getstarted.html#installation) (`>=23.10.1`)
2. Install any of [`Docker`](https://docs.docker.com/engine/installation/), [`Singularity`](https://www.sylabs.io/guides/3.0/user-guide/) (you can follow [this tutorial](https://singularity-tutorial.github.io/01-installation/)), [`Podman`](https://podman.io/), [`Shifter`](https://nersc.gitlab.io/development/shifter/how-to-use/) or [`Charliecloud`](https://hpc.github.io/charliecloud/) for full pipeline reproducibility _(you can use [`Conda`](https://conda.io/miniconda.html) both to install Nextflow itself and also to manage software within pipelines. Please only use it within pipelines as a last resort; see [docs](https://nf-co.re/usage/configuration#basic-configuration-profiles))_.
3. Download the pipeline and test it on a minimal dataset with a single command:
```bash
# for aligned reads
nextflow run sanger-tol/variantcalling -profile test,YOURPROFILE --outdir
# for unaligned reads
nextflow run sanger-tol/variantcalling -profile test_align,YOURPROFILE --outdir
```
Note that some form of configuration will be needed so that Nextflow knows how to fetch the required software. This is usually done in the form of a config profile (`YOURPROFILE` in the example command above). You can chain multiple config profiles in a comma-separated string.
> - The pipeline comes with config profiles called `docker`, `singularity`, `podman`, `shifter`, `charliecloud` and `conda` which instruct the pipeline to use the named tool for software management. For example, `-profile test,docker`.
> - Please check [nf-core/configs](https://github.com/nf-core/configs#documentation) to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use `-profile ` in your command. This will enable either `docker` or `singularity` and set the appropriate execution settings for your local compute environment.
> - If you are using `singularity`, please use the [`nf-core download`](https://nf-co.re/tools/#downloading-pipelines-for-offline-use) command to download images first, before running the pipeline. Setting the [`NXF_SINGULARITY_CACHEDIR` or `singularity.cacheDir`](https://www.nextflow.io/docs/latest/singularity.html?#singularity-docker-hub) Nextflow options enables you to store and re-use the images from a central location for future pipeline runs.
> - If you are using `conda`, it is highly recommended to use the [`NXF_CONDA_CACHEDIR` or `conda.cacheDir`](https://www.nextflow.io/docs/latest/conda.html) settings to store the environments in a central location for future pipeline runs.
4. Start running your own analysis!
```bash
nextflow run sanger-tol/variantcalling --input samplesheet.csv --outdir --fasta genome.fasta.gz -profile
```
## Credits
sanger-tol/variantcalling was originally written by [Guoying Qi](https://github.com/gq1).
We thank the following people for their extensive assistance in the development of this pipeline:
- [Priyanka Surana](https://github.com/priyanka-surana) for the pipeline design, code review and Nextflow technical supports.
- [Matthieu Muffato](https://github.com/muffato) for the pipeline design, code review and Nextflow technical supports.
We also acknowledge the work of [Damon-Lee Pointon](https://github.com/DLBPointon) for attempting to create an short read variant calling subworkflow.
## Contributions and Support
If you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).
For further information or help, don't hesitate to get in touch on the [Slack `#pipelines` channel](https://sangertreeoflife.slack.com/channels/pipelines). Please [create an issue](https://github.com/sanger-tol/variantcalling/issues/new/choose) on GitHub if you are not on the Sanger slack channel.
## Citations
If you use sanger-tol/variantcalling for your analysis, please cite it using the following doi: [10.5281/zenodo.7890527](https://doi.org/10.5281/zenodo.7890527)
An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.
This pipeline uses code and infrastructure developed and maintained by the [nf-core](https://nf-co.re) community, reused here under the [MIT license](https://github.com/nf-core/tools/blob/master/LICENSE).
> **The nf-core framework for community-curated bioinformatics pipelines.**
>
> Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.
>
> _Nat Biotechnol._ 2020 Feb 13. doi: [10.1038/s41587-020-0439-x](https://dx.doi.org/10.1038/s41587-020-0439-x).