Benchmarking of de novo assembly algorithms for Nanopore data reveals optimal performance of OLC approaches
dc.contributor.author | Cherukuri, Yesesri | |
dc.contributor.author | Janga, Sarath Chandra | |
dc.contributor.department | Department of Biohealth Informatics, School of Informatics and Computing | en_US |
dc.date.accessioned | 2016-09-19T19:37:27Z | |
dc.date.available | 2016-09-19T19:37:27Z | |
dc.date.issued | 2016 | |
dc.description.abstract | Improved DNA sequencing methods have transformed the field of genomics over the last decade. This has become possible due to the development of inexpensive short read sequencing technologies which have now resulted in three generations of sequencing platforms. More recently, a new fourth generation of Nanopore based single molecule sequencing technology, was developed based on MinION® sequencer which is portable, inexpensive and fast. It is capable of generating reads of length greater than 100 kb. Though it has many specific advantages, the two major limitations of the MinION reads are high error rates and the need for the development of downstream pipelines. The algorithms for error correction have already emerged, while development of pipelines is still at nascent stage. | en_US |
dc.eprint.version | Final published version | en_US |
dc.identifier.citation | Cherukuri, Y., & Janga, C. S. (2016). Benchmarking of de novo assembly algorithms for Nanopore data reveals optimal performance of OLC approaches. BMC Genomics, 17(7), 95–105. http://doi.org/10.1186/s12864-016-2895-8 | en_US |
dc.identifier.uri | https://hdl.handle.net/1805/10988 | |
dc.publisher | Biomed Central | en_US |
dc.relation.isversionof | 10.1186/s12864-016-2895-8 | en_US |
dc.relation.journal | BMC Genomics | en_US |
dc.rights | Attribution 3.0 United States | |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/us/ | |
dc.source | Publisher | en_US |
dc.subject | Contigs | en_US |
dc.subject | De Bruijn | en_US |
dc.subject | De novo assembly | en_US |
dc.subject | Greedy Extension graph | en_US |
dc.subject | N50 | en_US |
dc.subject | Nanopore | en_US |
dc.subject | Oxford Nanopore | en_US |
dc.title | Benchmarking of de novo assembly algorithms for Nanopore data reveals optimal performance of OLC approaches | en_US |
dc.type | Article | en_US |
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