A memory-efficient algorithm to obtain splicing graphs and de novo expression estimates from de bruijn graphs of RNA-seq data

With the advance of high-throughput sequencing, it is feasible to study entire transcriptomes through the use of de novo sequence assembly algorithms. A popular strategy of these algorithms is to first construct an intermediate de Bruijn graph structure that represents the transcriptome. An additional step is performed to obtain predicted transcripts from the graph.