Speaker
Description
Alternative splicing (AS) is a major contributor to transcriptome and proteome diversity in health and disease. A plethora of tools has been developed for studying alternative splicing in RNA-seq data. Previous benchmarks focused on isoform quantification and mapping. They neglected event detection tools which arguably provide the most detailed insights into the alternative splicing process. DICAST offers a modular and extensible alternative splicing framework integrating eleven splice-aware mapping and eight event detection tools. We benchmark all of these extensively on simulated as well as whole blood RNA-seq data. We explore performance of these tools under increasing read depth, by simulated datasets of read depths 50, 100 and 200 million reads. We also explore performance of the tools on simulated datasets with 1 transcript per gene. 1 AS event for that transcript, to complex events on multiple transcripts per gene. The performance of event detection tools varies widely with no tool outperforming all others. DICAST allows researchers to employ a consensus approach to consider the most successful tools jointly in robust event detection. Finally, we propose the first reporting standard to unify existing formats and to guide future tool development.
