Benchmarking of de novo assembly algorithms for Nanopore data reveals optimal performance of OLC approaches

dc.contributor.authorCherukuri, Yesesri
dc.contributor.authorJanga, Sarath Chandra
dc.contributor.departmentDepartment of Biohealth Informatics, School of Informatics and Computingen_US
dc.date.accessioned2016-09-19T19:37:27Z
dc.date.available2016-09-19T19:37:27Z
dc.date.issued2016
dc.description.abstractImproved 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.versionFinal published versionen_US
dc.identifier.citationCherukuri, 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/s12864-016-2895-8en_US
dc.identifier.urihttps://hdl.handle.net/1805/10988
dc.publisherBiomed Centralen_US
dc.relation.isversionof10.1186/s12864-016-2895-8en_US
dc.relation.journalBMC Genomicsen_US
dc.rightsAttribution 3.0 United States
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/
dc.sourcePublisheren_US
dc.subjectContigsen_US
dc.subjectDe Bruijnen_US
dc.subjectDe novo assemblyen_US
dc.subjectGreedy Extension graphen_US
dc.subjectN50en_US
dc.subjectNanoporeen_US
dc.subjectOxford Nanoporeen_US
dc.titleBenchmarking of de novo assembly algorithms for Nanopore data reveals optimal performance of OLC approachesen_US
dc.typeArticleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
art_10.1186_s12864-016-2895-8.pdf
Size:
1.11 MB
Format:
Adobe Portable Document Format
Description:
Final Published Version
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.88 KB
Format:
Item-specific license agreed upon to submission
Description: