![]() Predicted fusions are then ‘in silico validated’ using FusionInspector, which performs a more refined exploration of the candidate fusion transcripts, runs Trinity to de novo assemble fusion transcripts from the RNA-Seq reads, and provides the evidence in a suitable format to facilitate visualization. The Trinity CTAT Fusion workflow involves first running STAR-Fusion to identify candidate fusion transcripts based on discordant read alignments. Note that the STAR-Fusion software incorporates FusionInspector and several companion utilities that will be used for fusion analysis. The tutorial below demonstrates the use of each of these utilities in identifying and characterizing cancer fusion transcripts. Tools leveraged within CTAT include STAR-Fusion, FusionInspector, and Trinity. ![]() The tools and comprehensive workflow for fusion study via Trinity CTAT is illustrated below: The Trinity Cancer Transcriptome Analysis Toolkit (CTAT) includes a suite of tools focused on identifying and characterizing fusion transcripts in cancer. ![]() Tutorial for the CTAT Fusion Toolkit, leveraging STAR-Fusion, FusionInspector, and Trinity
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