Sparc: a sparsity-based consensus algorithm for long erroneous sequencing reads
- Published
- Accepted
- Subject Areas
- Bioinformatics, Biotechnology, Computational Biology, Genomics, Computational Science
- Keywords
- Consensus Algorithm, Genome Assembly, Variant Discovery, Single Molecular Sequencing, Third Generation Sequencing Technology
- Copyright
- © 2015 Ye et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. Sparc: a sparsity-based consensus algorithm for long erroneous sequencing reads. PeerJ PrePrints 3:e1401v1 https://doi.org/10.7287/peerj.preprints.1401v1
Abstract
Motivation: The third generation sequencing (3GS) technology generates long sequences of thousands of bases. However, its error rates are estimated in the range of 15-40%, much higher than the previous generation (approximately 1%). Fundamental tasks such as genome assembly and variant calling require us to obtain high quality sequences from these long erroneous sequences. Results: In this paper we describe a versatile and efficient linear complexity consensus algorithm Sparc that builds a sparse k-mer graph using a collection of sequences from the same genomic region. The heaviest path approximates the most likely genome sequence (consensus) and is sought through a sparsity-induced reweighted graph. Experiments show that our algorithm can efficiently provide high-quality consensus sequences with error rate <0.5% using both PacBio and Oxford Nanopore sequencing technologies. Compared with the existing approaches, Sparc calculates the consensus with higher accuracy, uses 80% less memory, and is 5x faster, approximately. Availability: The source code is available for download at http://sourceforge.net/p/sparc-consensus/code/ and a testing dataset is available: https://www.dropbox.com/sh/trng8vdaeqywx1e/AAASJesLVAJZcbORkU9f4LuBa?dl=0 (Please copy the link to a browser to access if directly clicking the link fails)
Author Comment
This is a submission to PeerJ for review.