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- W1504604114 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." @default.
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- W1504604114 date "2015-05-29" @default.
- W1504604114 modified "2023-09-22" @default.
- W1504604114 title "SeedsGraph: an efficient assembler for next-generation sequencing data" @default.
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- W1504604114 doi "https://doi.org/10.1186/1755-8794-8-s2-s13" @default.
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