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ro-crate-metadata.json
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"description": "# NationalGenomicsInfrastructure/radqc\n\n## Introduction\n\n**NationalGenomicsInfrastructure/radqc** is a bioinformatics best-practice analysis pipeline for Pipeline for QC of RAD-seq data.\n\n- [Documentation](#documentation)\n- [Quick start](#quick-start)\n- [NGI data and usage](#ngi-data-and-usage)\n- [Contributions and Support](#contributions-and-support)\n- [Citations](#citations)\n\n## Documentation\n\nPlease see the more detailed [usage documentation](docs/README.md)\n\n## Quick start\n\n> [!NOTE]\n> 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\nTo test your nextflow / Docker / Singularity setup on your computer you can run the pipeline using test data:\n\n```\nnextflow run NationalGenomicsInfrastructure/radQC -profile <docker,singularity>,test -r master --outdir results\n```\n\nWhen you this test run is successfully completed, or if you elect to skip it you can start your analysis run. First by preparing a samplesheet with your input data that looks as follows:\n\n`samplesheet.csv`:\n\n```csv title=\"samplesheet.csv\"\nsample,population,fastq_1,fastq_2\nsample101,pop1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz\n```\n\nNow, you can run the pipeline using:\n\n```bash title=\"run.sh\"\nnextflow run NationalGenomicsInfrastructure/radqc \\\n -profile <docker/singularity/.../institute> \\\n --input samplesheet.csv \\\n --enzyme <enzyme> \\\n --outdir <OUTDIR> \\\n -r <master,v##.##>\n```\n\n> [!WARNING]\n> 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\n## NGI data and usage\n\nThis section describes parameter considerations when running this pipeline on data produced by [NGI Sweden](https://ngisweden.scilifelab.se/methods/rad-sequencing/), and additionally when running the pipeline on the Miarka cluster. Quick reference as of 2025-04-15 for running the pipeline:\n\n```bash title=\"run.sh\"\nnextflow run /path/to/NationalGenomicsInfrastructure-radqc/ \\\n--trim_truncate 130 \\\n--trim_head 5 \\\n--enzyme ecoRI \\\n--process_radtags_options='--disable-rad-check' \\\n--input samplesheet.csv \\\n--outdir ./results \\\n--project ngi2016004 \\\n-profile singularity \\\n-c /path/to/NationalGenomicsInfrastructure-radqc/configs/conf/uppmax.config\n```\n\nThere is a convenience [script](bin/samplesheet_gen.py) to generate a samplesheet that will search for `P???_???` named NGI samples:\n\n```bash\npython /path/to/NationalGenomicsInfrastructure-radqc/bin/samplesheet_gen.py /path/to/data/project_folder_with_fastqs/ samplsheet.csv\n```\n\nFor offline use the pipeline is downloaded using nf-core [tools](https://nf-co.re/tools) and including institutional configs specifically for Miarka/UPPMAX, e.g. `nf-core pipelines download -c yes -s singularity <pipeline name>`\n\n* `--trim_truncate 130` This is to trim the reads to a uniform length. Traditionally Stacks only supported uniform lengths, so consider skipping if the libraries have a much longer insert than 300 nt.\n* `--enzyme ecoRI` NGI rad-seq data made from digestion fragments of ecoRI\n* `--trim_head 5` EcoRI have a cut site / overhang (AATTC) that can lead to low complexity and low quality sequecing in the first 5 cycles. You can check if this the case by running fastQC on the raw data, but this parameter will trim the first 5 nts.\n* `--process_radtags_options='--disable-rad-check'` When we are trimming the cut site we need to instruct process_radtags to not check ecoRI sequences\n* `-profile singularity` Container system supported on UPPMAX\n\n\n## Credits\n\nNationalGenomicsInfrastructure/radqc was originally written by Remi-Andr\u00e9 Olsen.\n\nWe thank the following people for their extensive assistance in the development of this pipeline:\n\n\n## Contributions and Support\n\nIf you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).\n\n## Citations\n\nAn extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.\n\nThis 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/main/LICENSE).\n\n> **The nf-core framework for community-curated bioinformatics pipelines.**\n>\n> Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.\n>\n> _Nat Biotechnol._ 2020 Feb 13. doi: [10.1038/s41587-020-0439-x](https://dx.doi.org/10.1038/s41587-020-0439-x).\n",
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