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SeedsGraph: an efficient assembler for next-generation sequencing data.

ABSTRACT: DNA sequencing technology has been rapidly evolving, and produces a large number of short reads with a fast rising tendency. This has led to a resurgence of research in whole genome shotgun assembly algorithms. We start the assembly algorithm by clustering the short reads in a cloud computing framework, and the clustering process groups fragments according to their original consensus long-sequence similarity. We condense each group of reads to a chain of seeds, which is a kind of substring with reads aligned, and then build a graph accordingly. Finally, we analyze the graph to find Euler paths, and assemble the reads related in the paths into contigs, and then lay out contigs with mate-pair information for scaffolds. The result shows that our algorithm is efficient and feasible for a large set of reads such as in next-generation sequencing technology.

SUBMITTER: Wang C

PROVIDER: S-EPMC4460749 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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SeedsGraph: an efficient assembler for next-generation sequencing data.

Wang Chunyu C Guo Maozu M Liu Xiaoyan X Liu Yang Y Zou Quan Q

BMC medical genomics 20150529

DNA sequencing technology has been rapidly evolving, and produces a large number of short reads with a fast rising tendency. This has led to a resurgence of research in whole genome shotgun assembly algorithms. We start the assembly algorithm by clustering the short reads in a cloud computing framework, and the clustering process groups fragments according to their original consensus long-sequence similarity. We condense each group of reads to a chain of seeds, which is a kind of substring with ...[more]

PMID: 26044652

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