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. 2020 Dec 14;21:577. doi: 10.1186/s12859-020-03922-7

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© The Author(s) 2020

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 1 — Graphical representation of the annoFuse pipeline. RNA-seq data processed through STAR-RSEM and fusion calls generated by Arriba v1.1.0 and/or STAR-Fusion 1.5.0 are inputs for the pipeline. The fusion_standardization function standardizes calls from fusion callers to retain information regarding fused genes, breakpoints, reading frame information, as well as annotation from FusionAnnotator. Standardized fusion calls use fusion_filtering_QC to remove false positives such as fusions with low read support, annotated as read-throughs, found in normal and gene homolog databases and remove non-expressed fusions using expression_filter_fusion. Calls are annotated with annotate_fusion_calls to include useful biological features of interest (eg. Kinase, Tumor suppressor etc.) Project-specific filtering captures recurrent fused genes using functions to filter (shown in boxes) as well as putative driver fusion. Outputs available from annoFuse include TSV files of annotated and prioritized fusions, a PDF summary of fusions, recurrently-fused gene/fusion plots, and an HTML report. Finally, users can explore fusion data interactively using shinyFuse. (Created with BioRender.com)