Optimization of de novo transcriptome assembly from next-generation sequencing data

Transcriptome analysis has important applications in many biological fields. However, assembling a transcriptome without a known reference remains a challenging task requiring algorithmic improvements. We present two methods for substantially improving transcriptome de novo assembly. The first method relies on the observation that the use of a single k -mer length by current de novo assemblers is suboptimal to assemble transcriptomes where the...