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How does fusion gene detection thru RNA-seq compare to FDA approved kits? ymc RNA Sequencing 0 09-11-2013 05:59 PM

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Old 02-15-2018, 11:53 AM   #1
uhrigs
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Default Arriba: Fast and accurate gene fusion detection from RNA-Seq data

Dear all,

We developed an algorithm called "Arriba" to detect gene fusions from RNA-Seq data of tumor samples. It is based on the ultrafast STAR aligner (https://github.com/alexdobin/STAR) and the post-alignment runtime is typically just ~2 minutes. Hence, fusion detection comes at virtually no cost, since the alignment of FastQ reads is a task that needs to be done anyway in a typical RNA-Seq workflow.

But Arriba is not only fast, it is also very accurate: It is currently the best-performing algorithm in the ongoing ICGC-TCGA DREAM SMC Challenge about gene fusion algorithms (final results pending):
https://www.synapse.org/#!Synapse:sy...89/wiki/423306

Some more highlights:
- ability to detect intergenic and intronic breakpoints
- ability to detect exon duplications/inversions
- utilization of structural variants obtained from whole-genome sequencing
- filtering of transcript variants observed in healthy tissue
- comprehensive manual available at http://arriba.readthedocs.io/
- simple installation routine; especially, if you already use STAR

We would be glad, if you could give it a try, and are happy to receive feedback!
Please visit the homepage to download the code or in case you need help:
https://github.com/suhrig/arriba/

Best regards,
Sebastian
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Old 02-21-2018, 01:56 AM   #2
pli
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Hi Sebastian,

has, or will this method be published? Would be nice. Cheers,

P
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Old 02-21-2018, 01:37 PM   #3
uhrigs
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Yes, the method will certainly be published. I have just started working on the manuscript. Stay tuned ...
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Old 04-18-2019, 05:24 AM   #4
uhrigs
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We are happy to announce that Arriba won first place in the DREAM SMC-RNA Challenge! The final results can be viewed here (requires a free Synapse account): https://www.synapse.org/#!Synapse:sy...89/wiki/588511 As a result, Arriba will be presented at the DREAM Challenge satellite workshop of the RECOMB conference in Washington, D.C. beginning of next month.

In addition, since our first announcement on this forum a year ago, many improvements have been made to Arriba:

- streamlined workflow, which makes Arriba even faster and easier to implement
- installation via Docker, Singularity, and Bioconda
- automatic generation of publication-quality figures
- prediction of peptide sequences and retained protein domains
- CRAM support
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Old 11-12-2020, 07:41 AM   #5
uhrigs
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Version 2 of our gene fusion detection algorithm Arriba is available. It comes with a number of new features and enhancements:

- detect viral integration sites
- detect fusions supported by multi-mapping reads (e.g., CIC-DUX4, NPM1-ALK)
- detect internal tandem duplications (e.g., FLT3, BCOR, ERBB2)
- support for mouse (mm10)
- more comprehensive annotation
- speed improvements
- accuracy enhancements

As usual, the code is available on GitHub: https://github.com/suhrig/arriba/releases

Documentation and installation instructions are available on ReadTheDocs: https://arriba.readthedocs.io/en/latest/quickstart/
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Old 03-01-2021, 02:32 PM   #6
anjukanda
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Hi Sebastian,

I have recently installed Arriba v 2.1.0 and struggling with the statistics about the number of supporting reads in my pdfs that are being generated. Could you please suggest me what to do in order to get the number of split reads in gene1 and no of split reads in gene 2?

Thanks in advance!
AK
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Old 03-03-2021, 09:53 AM   #7
uhrigs
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Hi Anju,

As discussed via mail, since Arriba version 2, the split read counts are not reported separately for gene1 and gene2 anymore in the visualization PDF. This change was made to be compatible with STAR-Fusion output, which does not report the numbers separately for gene1 and gene2.

If you have further questions, feel free to reach out to me via mail or the issue tracker on GitHub: https://github.com/suhrig/arriba/issues

Kind regards,
Sebastian
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Old 03-04-2021, 02:19 AM   #8
anjukanda
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Hi Sebastian,

Thank you for your response. I wasn't sure whether you would reply to my email. Hencewhy I tried on seqanswers. I have send the job for running and it still in the queue. I will let you know when its done on the email.

Thanks again!

Best regards,
Anju
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Old 03-20-2021, 08:44 AM   #9
uhrigs
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We are proud to announce that our manuscript about Arriba has been published in this month's issue of the Genome Research journal. From now on, please cite the following article if you use Arriba for published research:

Sebastian Uhrig, Julia Ellermann, Tatjana Walther, Pauline Burkhardt, Martina Fröhlich, Barbara Hutter, Umut H. Toprak, Olaf Neumann, Albrecht Stenzinger, Claudia Scholl, Stefan Fröhling and Benedikt Brors: Accurate and efficient detection of gene fusions from RNA sequencing data. Genome Research. March 2021 31: 448-460; Published in Advance January 13, 2021. doi: 10.1101/gr.257246.119
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