cloudSPAdes: assembly of synthetic long reads using de Bruijn graphs.
Ivan Tolstoganov, Anton Bankevich, Zhoutao Chen, Pavel A Pevzner
Author Information
Ivan Tolstoganov: Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia.
Anton Bankevich: Department of Computer Science and Engineering, University of California at San Diego, La Jolla, CA, USA.
Zhoutao Chen: Universal Sequencing Technology Corporation, Carlsbad, CA, USA.
Pavel A Pevzner: Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia.
MOTIVATION: The recently developed barcoding-based synthetic long read (SLR) technologies have already found many applications in genome assembly and analysis. However, although some new barcoding protocols are emerging and the range of SLR applications is being expanded, the existing SLR assemblers are optimized for a narrow range of parameters and are not easily extendable to new barcoding technologies and new applications such as metagenomics or hybrid assembly. RESULTS: We describe the algorithmic challenge of the SLR assembly and present a cloudSPAdes algorithm for SLR assembly that is based on analyzing the de Bruijn graph of SLRs. We benchmarked cloudSPAdes across various barcoding technologies/applications and demonstrated that it improves on the state-of-the-art SLR assemblers in accuracy and speed. AVAILABILITY AND IMPLEMENTATION: Source code and installation manual for cloudSPAdes are available at https://github.com/ablab/spades/releases/tag/cloudspades-paper. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
