Tool: Arriba: Fast and accurate gene fusion detection from RNA-Seq data
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15 months ago by
uhrigs80 wrote:

Arriba is a command-line tool for the detection of gene fusions from RNA-Seq data of tumor samples. It is based on the ultrafast STAR aligner 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.

Arriba has been submitted to the DREAM SMC RNA Challenge, an international competition organized by ICGC, TCGA, IBM, and Sage Bionetworks to determine the current gold standard for the detection of gene fusions from RNA-Seq data. As of round 4, Arriba is the best-performing algorithm.

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
  • 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:

ADD COMMENTlink modified 4 weeks ago • written 15 months ago by uhrigs80
gravatar for uhrigs
4 weeks ago by
uhrigs80 wrote:

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):!Synapse:syn2813589/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
ADD COMMENTlink written 4 weeks ago by uhrigs80
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