Next generation sequencing of cellular RNA is making it possible to characterize genes and alternative splicing in unprecedented detail. However, designing bioinformatics tools to capture splicing variation accurately has proven difficult. Current programs find major isoforms of a gene but miss finer splicing variations, or are sensitive but highly imprecise.
Researchers from Johns Hopkins School of Medicine present CLASS, a novel open source tool for accurate genome-guided transcriptome assembly from RNA-seq reads. CLASS employs a splice graph to represent a gene and its splice variants, combined with a linear program to determine an accurate set of exons and efficient splice graph-based transcript selection algorithms. When compared against reference programs, CLASS had the best overall accuracy and could detect up to twice as many splicing events with precision similar to the best reference program. Notably, it was the only tool that produced consistently reliable transcript models for a wide range of applications and sequencing strategies, including very large data sets and ribosomal RNA-depleted samples. Lightweight and multi-threaded, CLASS required <3GB RAM and less than one day to analyze a 350 million read set, and is an excellent choice for transcriptomics studies, from clinical RNA sequencing, to alternative splicing analyses, and to the annotation of new genomes.
Availability – CLASS is available free of charge for all and under a GNU GPL license from: http://sourceforge.net/projects/Splicebox