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

ABSTRACT: 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 sequence coverage of transcripts is highly heterogeneous. We present the Multiple-k method in which various k-mer lengths are used for de novo transcriptome assembly. We demonstrate its good performance by assembling de novo a published next-generation transcriptome sequence data set of Aedes aegypti, using the existing genome to check the accuracy of

SUBMITTER: Surget-Groba Y 

PROVIDER: S-EPMC2945192 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature