→ Poster doi:10.7490/f1000research.1112725.1
Asma Bankapur 1, Timothy Ticke 1, Carrie Ganote 2, Ben Fulton 2, Tom Doak 2, Brian Haas 1, Aviv Regev 1
- Broad Institute
- Indiana University
Cancer transcriptome sequencing (RNA-Seq) has highlighted the extent of gene variation in cancer leading to unique cancer transcriptomes. We provide best known practices in cancer transcript analysis leveraging de novo
transcript reconstruction in form of simple, user-friendly Galaxy tools accessible to any cancer researcher. Currently available RNA-Seq analysis modules include: an ensemble of best-in-class fusion discovery tools, a mutation calling pipeline with cancer specific annotation, Trinity de novo
assembly and downstream analysis highlighted in Nature Protocols, lncRNA detection. Visualization for fusion and mutation tools is aided by IGV.js and for lncRNA detection we use web browser generated by Slncky for ortholog search within Galaxy framework.This is made available through our public Galaxy instance hosted by National Center for Genome Analysis Support at Indiana University. In addition, we would also like to highlight our in house implementation at KCO of RNASeq and single cell DropSeq pipelines in multisample mode which runs via an internal job runner.