{"id":51111470,"url":"https://github.com/nf-core/dartseq","last_synced_at":"2026-06-24T18:01:33.152Z","repository":{"id":361830198,"uuid":"1231814241","full_name":"nf-core/dartseq","owner":"nf-core","description":"Pipeline for m6A detection in RNAseq 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 \u003cpicture\u003e\n    \u003csource media=\"(prefers-color-scheme: dark)\" srcset=\"docs/images/nf-core-dartseq_logo_dark.png\"\u003e\n    \u003cimg alt=\"nf-core/dartseq\" src=\"docs/images/nf-core-dartseq_logo_light.png\"\u003e\n  \u003c/picture\u003e\n\u003c/h1\u003e\n\n[![Open in GitHub Codespaces](https://img.shields.io/badge/Open_In_GitHub_Codespaces-black?labelColor=grey\u0026logo=github)](https://github.com/codespaces/new/nf-core/dartseq)\n[![GitHub Actions CI Status](https://github.com/nf-core/dartseq/actions/workflows/nf-test.yml/badge.svg)](https://github.com/nf-core/dartseq/actions/workflows/nf-test.yml)\n[![GitHub Actions Linting Status](https://github.com/nf-core/dartseq/actions/workflows/linting.yml/badge.svg)](https://github.com/nf-core/dartseq/actions/workflows/linting.yml)[![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?labelColor=000000\u0026logo=Amazon%20AWS)](https://nf-co.re/dartseq/results)\n[![nf-test](https://img.shields.io/badge/unit_tests-nf--test-337ab7.svg)](https://www.nf-test.com)\n\n[![Nextflow](https://img.shields.io/badge/version-%E2%89%A525.04.0-green?style=flat\u0026logo=nextflow\u0026logoColor=white\u0026color=%230DC09D\u0026link=https%3A%2F%2Fnextflow.io)](https://www.nextflow.io/)\n[![nf-core template version](https://img.shields.io/badge/nf--core_template-3.5.2-green?style=flat\u0026logo=nfcore\u0026logoColor=white\u0026color=%2324B064\u0026link=https%3A%2F%2Fnf-co.re)](https://github.com/nf-core/tools/releases/tag/3.5.2)\n[![DOI](https://zenodo.org/badge/doi/10.5281/zenodo.XXXXXXX.svg)](https://doi.org/10.5281/zenodo.XXXXXXX)\n[![run with conda](http://img.shields.io/badge/run%20with-conda-3EB049?labelColor=000000\u0026logo=anaconda)](https://docs.conda.io/en/latest/)\n[![run with docker](https://img.shields.io/badge/run%20with-docker-0db7ed?labelColor=000000\u0026logo=docker)](https://www.docker.com/)\n[![run with singularity](https://img.shields.io/badge/run%20with-singularity-1d355c.svg?labelColor=000000)](https://sylabs.io/docs/)\n[![Launch on Seqera Platform](https://img.shields.io/badge/Launch%20%F0%9F%9A%80-Seqera%20Platform-%234256e7)](https://cloud.seqera.io/launch?pipeline=https://github.com/nf-core/dartseq)\n\n[![Get help on Slack](http://img.shields.io/badge/slack-nf--core%20%23dartseq-4A154B?labelColor=000000\u0026logo=slack)](https://nfcore.slack.com/channels/dartseq)[![Follow on Bluesky](https://img.shields.io/badge/bluesky-%40nf__core-1185fe?labelColor=000000\u0026logo=bluesky)](https://bsky.app/profile/nf-co.re)[![Follow on Mastodon](https://img.shields.io/badge/mastodon-nf__core-6364ff?labelColor=FFFFFF\u0026logo=mastodon)](https://mstdn.science/@nf_core)[![Watch on YouTube](http://img.shields.io/badge/youtube-nf--core-FF0000?labelColor=000000\u0026logo=youtube)](https://www.youtube.com/c/nf-core)\n\n## Introduction\n\n**nf-core/dartseq** is a workflow for DART-seq style RNA sequencing analyses with optional RNA editing downstream steps.\nIt accepts single-end or paired-end FASTQ input, performs read QC and alignment, and can run Bullseye- and RustQC-based\npost-processing. Standard outputs include per-sample QC reports, alignments, MultiQC summaries, and optional edited-site tables.\n\n![nf-core/dartseq workflow overview](docs/images/dartseq_metromap.png)\n\nWorkflow overview:\n\n1. Parse and validate the input samplesheet.\n2. Trim reads with `fastp` or `Trim Galore` (or skip trimming if requested).\n3. Run per-sample quality control with [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).\n4. Build or use provided aligner references (STAR or HISAT2).\n5. Align reads and produce sorted BAM files plus index files.\n6. Run optional Bullseye editing analysis:\n   parse BAM, summarize sites, quantify edits, compare against controls, and optionally RAC filter / gather sites / GLM.\n7. Run optional RustQC summaries on alignments.\n8. Aggregate run-wide summaries and software versions with [MultiQC](http://multiqc.info/).\n\n## Usage\n\n\u003e [!NOTE]\n\u003e 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.\n\nPrepare a samplesheet with at least `sample`, `fastq_1`, and `fastq_2` columns.\nFor single-end data, leave `fastq_2` empty.\n\nNow, you can run the pipeline using:\n\n```bash\nnextflow run nf-core/dartseq \\\n   -profile \u003cdocker/singularity/.../institute\u003e \\\n   --input samplesheet.csv \\\n   --outdir \u003cOUTDIR\u003e\n```\n\n\u003e [!WARNING]\n\u003e 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).\n\nFor 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).\n\n## Pipeline output\n\nTo 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.\nFor more details about the output files and reports, please refer to the\n[output documentation](https://nf-co.re/dartseq/output).\n\n## Credits\n\nnf-core/dartseq was originally written by Mathieu Flamand, Olga Brovkina, Joana Pimenta Bernardes, Fatemeh Nasehi.\n\nWe thank the following people for their extensive assistance in the development of this pipeline:\n\n- The nf-core maintainers and community contributors who helped evolve the template integration and testing strategy.\n\n## Contributions and Support\n\nIf you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).\n\nFor 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)).\n\n## Citations\n\nIf this pipeline is used in a publication, cite the nf-core framework below and the software references in `CITATIONS.md`.\nAfter the first release, update the placeholder DOI `10.5281/zenodo.XXXXXXX` in this README with the pipeline Zenodo DOI.\n\nAn extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.\n\nYou can cite the `nf-core` publication as follows:\n\n\u003e **The nf-core framework for community-curated bioinformatics pipelines.**\n\u003e\n\u003e Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso \u0026 Sven Nahnsen.\n\u003e\n\u003e _Nat Biotechnol._ 2020 Feb 13. doi: [10.1038/s41587-020-0439-x](https://dx.doi.org/10.1038/s41587-020-0439-x).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnf-core%2Fdartseq","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnf-core%2Fdartseq","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnf-core%2Fdartseq/lists"}