Understanding the occurrence and regulation of alternative splicing (AS) is a key task towards explaining the regulatory processes that shape the complex transcriptomes of higher eukaryotes. With the advent of high-throughput sequencing of RNA (RNA-Seq), the diversity of AS transcripts could be measured at an unprecedented depth. Although the catalog of known AS events has grown ever since, novel transcripts are commonly observed when working with less well annotated organisms, in the context of disease, or within large populations. Whereas an identification of complete transcripts is technically challenging and computationally expensive, focusing on single splicing events as a proxy for transcriptome characteristics is fruitful and sufficient for a wide range of analyses.
Researchers at the Sloan Kettering Institute have devloped SplAdder, an alternative splicing toolbox, that takes RNA-Seq alignments and an annotation file as input to:
- augment the annotation based on RNA-Seq evidence,
- identify alternative splicing events present in the augmented annotation graph,
- quantify and confirm these events based on the RNA-Seq data, and
- test for significant quantitative differences between samples.
Thereby, the main focus lies on performance, accuracy and usability.
SplAdder Analysis Flowchart
The main steps of the SplAdder workfow consist of (1) integrating annotation information and RNA-Seq data, (2) generating an augmented splicing graph from the integrated data, (3) extraction of splicing events from that graph, (4) quantifying the extracted events, and optionally (5) the differential analysis between samples and producing visualizations.
Availability – Source code and documentation are available for download at http://github.com/ratschlab/spladder. Example data, introductory information and a small tutorial are accessible via http://bioweb.me/spladder.