2007
DOI: 10.1093/bioinformatics/btm451
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Extending assembly of short DNA sequences to handle error

Abstract: http://152.2.15.114/~labweb/VCAKE

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Cited by 220 publications
(129 citation statements)
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“…40 The success of the recently introduced NGS assemblers is mainly caused by the development of pragmatic engineering and heuristics on assembly algorithms. 39 Some of the tools, such as SSAKE, 41 SHARCGS, 42 VCAKE, 43 and QSRA, 44 work by using greedy graph strategy. Programs applying this algorithm undertake one basic operation: iterative extension (that is, given any read or contig, it will merge with the one with the largest overlap).…”
Section: Assembly Strategiesmentioning
confidence: 99%
See 1 more Smart Citation
“…40 The success of the recently introduced NGS assemblers is mainly caused by the development of pragmatic engineering and heuristics on assembly algorithms. 39 Some of the tools, such as SSAKE, 41 SHARCGS, 42 VCAKE, 43 and QSRA, 44 work by using greedy graph strategy. Programs applying this algorithm undertake one basic operation: iterative extension (that is, given any read or contig, it will merge with the one with the largest overlap).…”
Section: Assembly Strategiesmentioning
confidence: 99%
“…Programs applying this algorithm undertake one basic operation: iterative extension (that is, given any read or contig, it will merge with the one with the largest overlap). The three programs (SSAKE, VCAKE and QSRA) have been developed to handle imperfectly matching reads, 41,43,44 whereas SHARCGS is widely used on uniform-length, high-coverage and unpaired short reads. QSRA, the most recently developed software in this category, has an advantage in quality-value scores to help users deal with base call errors.…”
Section: Assembly Strategiesmentioning
confidence: 99%
“…As an alternative, a prefix tree-based approach was introduced by Warren et al (2007) with their early work on SSAKE. This paradigm was also followed in the VCAKE algorithm by Jeck et al (2007), and in the SHARCGS algorithm by Dohm et al (2007). On a third branch, Edena (Hernandez et al 2008) was an adaptation of the traditional overlap-layout-consensus model to short reads.…”
mentioning
confidence: 99%
“…The overlap-and-extend approach, e.g., SSAKE [6], VCAKE [7] and SHARCGS [8], first determines overlapped reads, i.e., the suffix of a read is the same as the prefix IDBA-MTP Extension of IDBA for assembling prokaryotic metatranscriptomic data. It assembles reads by applying known protein reference sequences.…”
Section: Existing Approachesmentioning
confidence: 99%