RNA-seq provides an efficient and sensitive methodology to identify fusion transcripts in cancer tissues. Chimeric reads mapping across two different genes represent potential gene fusions. Various methodologies have been implemented in the detection of gene fusions by RNA-seq. Here we describe a general methodology used in processing and filtering of RNA-seq data, followed by filtering of multiple varieties of artifacts to nominate potentially relevant gene fusions. Functional relevance of gene fusions is assessed based on the predicted domain architecture of the putative fusion proteins.
Keywords: BLAT; FastQC; Open reading frame (ORF); Paired end reads; RNA sequencing; STAR; STAR Fusion.