# SplAdder: Identification, quantification and testing of alternative splicing events from RNA-Seq data

## TL;DR

SplAdder is a tool that identifies and quantifies alternative splicing events from RNA-Seq data to better understand transcriptome complexity.

## Contribution

SplAdder introduces a comprehensive pipeline for augmenting annotations, identifying, quantifying, and testing alternative splicing events.

## Key findings

- SplAdder augments gene annotations using RNA-Seq evidence.
- The tool identifies and quantifies alternative splicing events with statistical testing.
- It is useful for studying less annotated organisms and disease contexts.

## Abstract

Motivation: 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.

Results: We present SplAdder, an alternative splicing toolbox, that takes RNA-Seq alignments and an annotation file as input to i) augment the annotation based on RNA-Seq evidence, ii) identify alternative splicing events present in the augmented annotation graph, iii) quantify and confirm these events based on the RNA-Seq data, and iv) test for significant quantitative differences between samples. Thereby, our main focus lies on performance, accuracy and usability.

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.

Contact: andre.kahles@ratschlab.org, gunnar.ratsch@ratschlab.org