https://github.com/nf-core/dartseq
Pipeline for m6A detection in RNAseq data
https://github.com/nf-core/dartseq
dartseq nextflow nf-core pipeline rna-editing rnaseq workflow
Last synced: 6 days ago
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Pipeline for m6A detection in RNAseq data
- Host: GitHub
- URL: https://github.com/nf-core/dartseq
- Owner: nf-core
- License: mit
- Created: 2026-05-07T10:07:21.000Z (about 2 months ago)
- Default Branch: dev
- Last Pushed: 2026-06-01T11:54:16.000Z (29 days ago)
- Last Synced: 2026-06-01T13:24:52.359Z (29 days ago)
- Topics: dartseq, nextflow, nf-core, pipeline, rna-editing, rnaseq, workflow
- Language: Nextflow
- Homepage: https://nf-co.re/dartseq
- Size: 21.5 MB
- Stars: 0
- Watchers: 0
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATIONS.md
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README
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[](https://doi.org/10.5281/zenodo.XXXXXXX)
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## Introduction
**nf-core/dartseq** is a workflow for DART-seq style RNA sequencing analyses with optional RNA editing downstream steps.
It accepts single-end or paired-end FASTQ input, performs read QC and alignment, and can run Bullseye- and RustQC-based
post-processing. Standard outputs include per-sample QC reports, alignments, MultiQC summaries, and optional edited-site tables.
Workflow overview:
1. Parse and validate the input samplesheet.
2. Trim reads with `fastp` or `Trim Galore` (or skip trimming if requested).
3. Run per-sample quality control with [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
4. Build or use provided aligner references (STAR or HISAT2).
5. Align reads and produce sorted BAM files plus index files.
6. Run optional Bullseye editing analysis:
parse BAM, summarize sites, quantify edits, compare against controls, and optionally RAC filter / gather sites / GLM.
7. Run optional RustQC summaries on alignments.
8. Aggregate run-wide summaries and software versions with [MultiQC](http://multiqc.info/).
## Usage
> [!NOTE]
> If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/usage/installation) on how to set-up Nextflow. Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline) with `-profile test` before running the workflow on actual data.
Prepare a samplesheet with at least `sample`, `fastq_1`, and `fastq_2` columns.
For single-end data, leave `fastq_2` empty.
Now, you can run the pipeline using:
```bash
nextflow run nf-core/dartseq \
-profile \
--input samplesheet.csv \
--outdir
```
> [!WARNING]
> Please provide pipeline parameters via the CLI or Nextflow `-params-file` option. Custom config files including those provided by the `-c` Nextflow option can be used to provide any configuration _**except for parameters**_; see [docs](https://nf-co.re/docs/usage/getting_started/configuration#custom-configuration-files).
For more details and further functionality, please refer to the [usage documentation](https://nf-co.re/dartseq/usage) and the [parameter documentation](https://nf-co.re/dartseq/parameters).
## Pipeline output
To see the results of an example test run with a full size dataset refer to the [results](https://nf-co.re/dartseq/results) tab on the nf-core website pipeline page.
For more details about the output files and reports, please refer to the
[output documentation](https://nf-co.re/dartseq/output).
## Credits
nf-core/dartseq was originally written by Mathieu Flamand, Olga Brovkina, Joana Pimenta Bernardes, Fatemeh Nasehi.
We thank the following people for their extensive assistance in the development of this pipeline:
- The nf-core maintainers and community contributors who helped evolve the template integration and testing strategy.
## 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 `#dartseq` channel](https://nfcore.slack.com/channels/dartseq) (you can join with [this invite](https://nf-co.re/join/slack)).
## Citations
If this pipeline is used in a publication, cite the nf-core framework below and the software references in `CITATIONS.md`.
After the first release, update the placeholder DOI `10.5281/zenodo.XXXXXXX` in this README with the pipeline Zenodo DOI.
An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.
You can cite the `nf-core` publication as follows:
> **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).