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TrinityFusion leverages chimeric and unmapped reads to assemble fusion transcripts and transcripts of likely foreign origin (microbes and viruses), as a way of facilitating analysis of cancer transcriptomes.
TrinityFusion performs de novo transcriptome assembly from RNA-seq data using Trinity, and uses GMAP to identify candidate fusion transcripts. Bowtie2 is finally used to capture the reads that support the fusion, and fusion candidates are filtered according to evidence support and characteristics of the fusion gene partners. An overview of the process is illustrated below:
TrinityFusion has three execution modes:
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TrinityFusion-D uses all input reads for de novo assembly followed by fusion detection.
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TrinityFusion-C uses only chimeric reads identified by the STAR aligner for de novo assembly and subsequent fusion detection.
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TrinityFusion-UC uses both the chimeric reads and reads that do not map to the genome as per the STAR aligner for de novo reconstruction followed by fusion detection.
TrinityFusion-UC has been found to be most generally useful for both fusion detection and exploring the assembled unmapped reads for potential transcripts of foreign origin, such as tumor viruses and microbes.
TrinityFusion can be downloaded from the TrinityFusion Releases site. Simply unpack the code and it's ready to use (no compilation necessary).
There are, however, other software dependencies:
Preferably, user our TrinityFusion Docker Image, which comes with everything it needs fully installed. The Dockerfile is included in the TrinityFusion source distribution, for those curious to see the full installation routine for building the Docker image.