Sparc: a sparsity-based consensus algorithm for long erroneous ...
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Sparc: a sparsity-based consensus algorithm for long erroneous ...
Jun 8, 2016 - efficient linear complexity consensus algorithm Sparc that builds a sparse k-mer graph using a collection of sequences from the same genomic ...
A peer-reviewed version of this preprint was published in PeerJ on 8 June 2016. View the peer-reviewed version (peerj.com/articles/2016), which is the preferred citable publication unless you specifically need to cite this preprint. Ye C, Ma Z. (2016) Sparc: a sparsity-based consensus algorithm for long erroneous sequencing reads. PeerJ 4:e2016 https://doi.org/10.7717/peerj.2016
Sparc: a sparsity-based consensus algorithm for long erroneous sequencing reads Chengxi Ye, Sam Ma
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
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