nf-core/rnafusion

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Introduction

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.

The pipeline requires >=16 CPU cores and >=30GB RAM

For available parameters or help run:

nextflow run nf-core/rnafusion --help

Quick Start

i. Install nextflow

ii. Install either Docker or Singularity for full pipeline reproducibility (please only use Conda as a last resort; see docs)

iii. Download references for all tools

nextflow run nf-core/rnafusion/download-references.nf -profile <docker/singularity/institute> \
  --download_all \
  --outdir <PATH> \
  --cosmic_usr <COSMIC_USER> --cosmic_passwd <COSMIC_PASSWD>

Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use -profile <institute> in your command. This will enable either docker or singularity and set the appropriate execution settings for your local compute environment.

iv. Start running your own analysis!

nextflow run nf-core/rnafusion -profile <docker/singularity/institute> \
  --reads '*_R{1,2}.fastq.gz' \
  --genomes_base 'reference_path_from_above'
  --arriba --star_fusion --fusioncatcher --ericscript --pizzly --squid \
  --arriba_vis --fusion_inspector

See usage docs for all of the available options when running the pipeline.

Documentation

The nf-core/rnafusion pipeline comes with documentation about the pipeline, found in the docs/ directory:

1. Installation
2. Pipeline configuration
   • Download references
   • Local installation
   • Adding your own system config
3. Running the pipeline
4. Output and how to interpret the results
5. Troubleshooting

Use predefined configuration for desired Institution cluster provided at nfcore/config repository.

Credits

This pipeline was originally written by Martin Proks (@matq007) in collaboration with Karolinska Institutet, SciLifeLab and University of Southern Denmark as a master thesis. This is a follow-up development started by Rickard Hammarén (@Hammarn).

Special thanks goes to all supervisors:

• Assoc. Prof. Teresita Díaz de Ståhl, PhD
• MD. Monica Nistér, PhD
• Maxime U Garcia, PhD
• Szilveszter Juhos
• Phil Ewels, PhD
• Assoc. Prof. Lars Grøntved, PhD

Tool References

• STAR-Fusion: Fast and Accurate Fusion Transcript Detection from RNA-Seq Brian Haas, Alexander Dobin, Nicolas Stransky, Bo Li, Xiao Yang, Timothy Tickle, Asma Bankapur, Carrie Ganote, Thomas Doak, Natalie Pochet, Jing Sun, Catherine Wu, Thomas Gingeras, Aviv Regev bioRxiv 120295; doi: https://doi.org/10.1101/120295
• D. Nicorici, M. Satalan, H. Edgren, S. Kangaspeska, A. Murumagi, O. Kallioniemi, S. Virtanen, O. Kilkku, FusionCatcher – a tool for finding somatic fusion genes in paired-end RNA-sequencing data, bioRxiv, Nov. 2014, DOI:10.1101/011650
• Benelli M, Pescucci C, Marseglia G, Severgnini M, Torricelli F, Magi A. Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript. Bioinformatics. 2012; 28(24): 3232-3239.
• Fusion detection and quantification by pseudoalignment Páll Melsted, Shannon Hateley, Isaac Charles Joseph, Harold Pimentel, Nicolas L Bray, Lior Pachter, bioRxiv 166322; doi: https://doi.org/10.1101/166322
• SQUID: transcriptomic structural variation detection from RNA-seq Cong Ma, Mingfu Shao and Carl Kingsford, Genome Biology, 2018, doi: https://doi.org/10.1186/s13059-018-1421-5
• Fusion-Inspector download: https://github.com/FusionInspector
• fusion-report download: https://github.com/matq007/fusion-report; doi: https://doi.org/10.5281/zenodo.3520171
• FastQC download: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/
• MultiQC Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics , 32(19), 3047–3048. https://doi.org/10.1093/bioinformatics/btw354 Download: https://multiqc.info/

Contributions and Support

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

For further information or help, don’t hesitate to get in touch on Slack (you can join with this invite).

Citation

If you use nf-core/rnafusion for your analysis, please cite it using the following doi: 10.5281/zenodo.151721952

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.
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