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chimeraviz: a tool for visualizing chimeric RNA.

Stian Lågstad1,2,3, Sen Zhao1,3, Andreas M Hoff1,3

  • 1Department of Molecular Oncology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway.

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|May 20, 2017
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Summary
This summary is machine-generated.

High-throughput RNA sequencing helps detect fusion transcripts, but often yields false discoveries. The chimeraviz R package visualizes chimeric RNA data, integrating genomic features to improve fusion detection accuracy.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • High-throughput RNA sequencing advances fusion transcript detection.
  • Current fusion detection software often has a high false discovery rate.

Purpose of the Study:

  • To present chimeraviz, a Bioconductor package for automated chimeric RNA visualization.
  • To aid in prioritizing fusion detection results by integrating RNA data with genomic features.

Main Methods:

  • Developed chimeraviz as an R package available via Bioconductor.
  • Ensured compatibility with nine different fusion-finder tools (deFuse, EricScript, InFusion, JAFFA, FusionCatcher, FusionMap, PRADA, SOAPfuse, STAR-FUSION).

Main Results:

  • chimeraviz automates the creation of chimeric RNA visualizations.
  • The package facilitates the integration of RNA sequencing data with known genomic features.

Conclusions:

  • chimeraviz provides a visualization framework to improve the accuracy of fusion transcript detection.
  • This tool helps overcome the high false discovery rate associated with current RNA sequencing analysis software.