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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing
| Date | Stars |
|---|---|
| 2026-07-24 | 583 |
| 2026-07-25 | 587 |
| 2026-07-28 | 588 |
| 2026-07-30 | 589 |
| 2026-08-06 | 589 |
Today
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Momentum
15.0
growth rate 0.00%/day
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[](https://github.com/codespaces/new/nf-core/sarek)
[](https://github.com/nf-core/sarek/actions/workflows/nf-test.yml)
[](https://github.com/nf-core/sarek/actions/workflows/linting.yml)
[](https://nf-co.re/sarek/results)
[](https://doi.org/10.5281/zenodo.3476425)
[](https://www.nf-test.com)
[](https://www.nextflow.io/)
[](https://github.com/nf-core/tools/releases/tag/3.5.1)
[](https://docs.conda.io/en/latest/)
[](https://www.docker.com/)
[](https://sylabs.io/docs/)
[](https://cloud.seqera.io/launch?pipeline=https://github.com/nf-core/sarek)
[](https://nfcore.slack.com/channels/sarek)
[](https://bsky.app/profile/nf-co.re)
[](https://mstdn.science/@nf_core)
[](https://www.youtube.com/c/nf-core)
## Introduction
**nf-core/sarek** is a workflow designed to detect variants on whole genome or targeted sequencing data. Initially designed for Human, and Mouse, it can work on any species with a reference genome. Sarek can also handle tumour / normal pairs and could include additional relapses.
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 AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark beExcerpt of 15,297 characters
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Adam Talbot · @seqeralabs · United Kingdom
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:b5683850427e23e3, topic:workflow
matched fp:b5683850427e23e3, topic:bioinformatics