Summary

Advances in high-throughput RNA sequencing have enabled more efficient detection of fusion transcripts, but the technology and associated software used for fusion detection from sequencing data often yield a high false discovery rate. Good prioritization of the results is important, and this can be helped by a visualization framework that automatically integrates RNA data with known genomic features. Here we present chimeraviz, a Bioconductor package that automates the creation of chimeric RNA visualizations. The package supports input from nine different fusion-finder tools: deFuse, EricScript, InFusion, JAFFA, FusionCatcher, FusionMap, PRADA, SOAPfuse and STAR-FUSION.

Availability and implementation

chimeraviz is an R package available via Bioconductor (https://bioconductor.org/packages/release/bioc/html/chimeraviz.html) under Artistic-2.0. Source code and support is available at GitHub (https://github.com/stianlagstad/chimeraviz).

Supplementary information

Supplementary data are available at Bioinformatics online.

© The Author 2017. Published by Oxford University Press.
2017
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