Ka-Kit Lam1, Kurt LaButti2, Asif Khalak3, David Tse4. 1. Department of Electrical Engineering and Computer Sciences, UC Berkeley. 2. U.S. Department of Energy Joint Genome Institute, Walnut Creek. 3. Pacific Biosciences, Menlo Park, and. 4. Department of Electrical Engineering and Computer Sciences, UC Berkeley, Department of Electrical Engineering, Stanford University, Palo Alto, CA, USA.
Abstract
UNLABELLED: We introduce FinisherSC, a repeat-aware and scalable tool for upgrading de novo assembly using long reads. Experiments with real data suggest that FinisherSC can provide longer and higher quality contigs than existing tools while maintaining high concordance. AVAILABILITY AND IMPLEMENTATION: The tool and data are available and will be maintained at http://kakitone.github.io/finishingTool/ CONTACT: : dntse@stanford.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
UNLABELLED: We introduce FinisherSC, a repeat-aware and scalable tool for upgrading de novo assembly using long reads. Experiments with real data suggest that FinisherSC can provide longer and higher quality contigs than existing tools while maintaining high concordance. AVAILABILITY AND IMPLEMENTATION: The tool and data are available and will be maintained at http://kakitone.github.io/finishingTool/ CONTACT: : dntse@stanford.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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