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dc.contributor.authorHon, Ting
dc.contributor.authorMars, Kristin
dc.contributor.authorYoung, Greg
dc.contributor.authorTsai, Yu-Chih
dc.contributor.authorKaralius, Joseph W.
dc.contributor.authorLandolin, Jane M.
dc.contributor.authorMaurer, Nicholas
dc.contributor.authorKudrna, David
dc.contributor.authorHardigan, Michael A.
dc.contributor.authorSteiner, Cynthia C.
dc.contributor.authorKnapp, Steven J.
dc.contributor.authorWare, Doreen
dc.contributor.authorShapiro, Beth
dc.contributor.authorPeluso, Paul
dc.contributor.authorRank, David R.
dc.date.accessioned2020-12-23T19:19:21Z
dc.date.available2020-12-23T19:19:21Z
dc.date.issued2020
dc.identifier.issn2052-4463
dc.identifier.doi10.1038/s41597-020-00743-4
dc.identifier.urihttp://hdl.handle.net/20.500.12634/809
dc.description.abstractThe PacBio® HiFi sequencing method yields highly accurate long-read sequencing datasets with read lengths averaging 10–25?kb and accuracies greater than 99.5%. These accurate long reads can be used to improve results for complex applications such as single nucleotide and structural variant detection, genome assembly, assembly of difficult polyploid or highly repetitive genomes, and assembly of metagenomes. Currently, there is a need for sample data sets to both evaluate the benefits of these long accurate reads as well as for development of bioinformatic tools including genome assemblers, variant callers, and haplotyping algorithms. We present deep coverage HiFi datasets for five complex samples including the two inbred model genomes Mus musculus and Zea mays, as well as two complex genomes, octoploid Fragaria?×?ananassa and the diploid anuran Rana muscosa. Additionally, we release sequence data from a mock metagenome community. The datasets reported here can be used without restriction to develop new algorithms and explore complex genome structure and evolution. Data were generated on the PacBio Sequel II System.
dc.language.isoen
dc.relation.urlhttps://www.nature.com/articles/s41597-020-00743-4
dc.rightsOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectRESEARCH
dc.subjectDATA PROCESSING
dc.subjectEVOLUTION
dc.subjectGENOMICS
dc.subjectMOUNTAIN YELLOW-LEGGED FROGS
dc.titleHighly accurate long-read HiFi sequencing data for five complex genomes
dc.typeArticle
dc.source.journaltitleScientific Data
dc.source.volume7
dc.source.issue1
dc.source.beginpage399
dcterms.dateAccepted2020
refterms.dateFOA2021-01-14T22:51:51Z
html.description.abstractThe PacBio® HiFi sequencing method yields highly accurate long-read sequencing datasets with read lengths averaging 10–25?kb and accuracies greater than 99.5%. These accurate long reads can be used to improve results for complex applications such as single nucleotide and structural variant detection, genome assembly, assembly of difficult polyploid or highly repetitive genomes, and assembly of metagenomes. Currently, there is a need for sample data sets to both evaluate the benefits of these long accurate reads as well as for development of bioinformatic tools including genome assemblers, variant callers, and haplotyping algorithms. We present deep coverage HiFi datasets for five complex samples including the two inbred model genomes Mus musculus and Zea mays, as well as two complex genomes, octoploid Fragaria?×?ananassa and the diploid anuran Rana muscosa. Additionally, we release sequence data from a mock metagenome community. The datasets reported here can be used without restriction to develop new algorithms and explore complex genome structure and evolution. Data were generated on the PacBio Sequel II System.


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Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Except where otherwise noted, this item's license is described as Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.