Efficient sequence clustering for RNA-seq data without a reference genome

Abstract

New deep-sequencing technologies are applied to transcript sequencing (RNA-seq) for transcriptomic studies. However, current approaches are based on the availability of a reference genome sequence for read mapping. We present Passage, a method for efficient read clustering in the absence of a reference genome that allows sequencing-based comparative transcriptomic studies for currently unsequenced organisms. If the reference genome is available, our method can be used to reduce the computational effort involved in read mapping. Comparisons to microarray data show a correlation of 0.69, proving the validity of our approach.