NationalGenomicsInfrastructure/radqc

Introduction

NationalGenomicsInfrastructure/radqc is a bioinformatics best-practice analysis pipeline for Pipeline for QC of RAD-seq data.

• Documentation
• Quick start
• NGI data and usage
• Contributions and Support
• Citations

Documentation

Please see the more detailed usage documentation

Quick start

[!NOTE] If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

To test your nextflow / Docker / Singularity setup on your computer you can run the pipeline using test data:

nextflow run NationalGenomicsInfrastructure/radQC -profile <docker,singularity>,test -r master --outdir results

When 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:

samplesheet.csv:

csv title="samplesheet.csv" sample,population,fastq_1,fastq_2 sample101,pop1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz

Now, you can run the pipeline using:

bash title="run.sh" nextflow run NationalGenomicsInfrastructure/radqc \ -profile <docker/singularity/.../institute> \ --input samplesheet.csv \ --enzyme <enzyme> \ --outdir <OUTDIR> \ -r <master,v##.##>

[!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.

NGI data and usage

This section describes parameter considerations when running this pipeline on data produced by NGI Sweden, and additionally when running the pipeline on the Miarka cluster. Quick reference as of 2025-04-15 for running the pipeline:

bash title="run.sh" nextflow run /path/to/NationalGenomicsInfrastructure-radqc/ \ --trim_truncate 130 \ --trim_head 5 \ --enzyme ecoRI \ --process_radtags_options='--disable-rad-check' \ --input samplesheet.csv \ --outdir ./results \ --project ngi2016004 \ -profile singularity \ -c /path/to/NationalGenomicsInfrastructure-radqc/configs/conf/uppmax.config

There is a convenience script to generate a samplesheet that will search for P???_??? named NGI samples:

bash python /path/to/NationalGenomicsInfrastructure-radqc/bin/samplesheet_gen.py /path/to/data/project_folder_with_fastqs/ samplsheet.csv

For offline use the pipeline is downloaded using nf-core tools and including institutional configs specifically for Miarka/UPPMAX, e.g. nf-core pipelines download -c yes -s singularity <pipeline name>

• --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.
• --enzyme ecoRI NGI rad-seq data made from digestion fragments of ecoRI
• --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.
• --process_radtags_options='--disable-rad-check' When we are trimming the cut site we need to instruct process_radtags to not check ecoRI sequences
• -profile singularity Container system supported on UPPMAX

Credits

NationalGenomicsInfrastructure/radqc was originally written by Remi-André Olsen.

We thank the following people for their extensive assistance in the development of this pipeline:

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT 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.