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dc.contributor.authorFukasawa, Yoshinori
dc.contributor.authorErmini, Luca
dc.contributor.authorWang, Hai
dc.contributor.authorCarty, Karen
dc.contributor.authorCheung, Ming Sin
dc.date.accessioned2020-02-13T11:02:05Z
dc.date.available2020-02-13T11:02:05Z
dc.date.issued2020-02-12
dc.date.submitted2019-10-26
dc.identifier.citationFukasawa, Y., Ermini, L., Wang, H., Carty, K., & Cheung, M.-S. (2020). LongQC: A Quality Control Tool for Third Generation Sequencing Long Read Data. G3: Genes|Genomes|Genetics, g3.400864.2019. doi:10.1534/g3.119.400864
dc.identifier.doi10.1534/g3.119.400864
dc.identifier.urihttp://hdl.handle.net/10754/661513
dc.description.abstractWe propose LongQC as an easy and automated quality control tool for genomic datasets generated by third generation sequencing (TGS) technologies such as Oxford Nanopore technologies (ONT) and SMRT sequencing from Pacific Bioscience (PacBio). Key statistics were optimized for long read data, and LongQC covers all major TGS platforms. LongQC processes and visualizes those statistics automatically and quickly.
dc.description.sponsorshipThis work was supported by Core Labs of King Abdullah University of Science and Technology.
dc.publisherGenetics Society of America
dc.relation.urlhttp://g3journal.org/lookup/doi/10.1534/g3.119.400864
dc.relation.urlhttps://www.g3journal.org/content/ggg/early/2020/02/10/g3.119.400864.full.pdf
dc.rightsArchived with thanks to G3 (Bethesda, Md.)
dc.titleLongQC: A Quality Control Tool for Third Generation Sequencing Long Read Data.
dc.typeArticle
dc.contributor.departmentBioinformatics
dc.contributor.departmentSanger and Third Generation Sequencing
dc.contributor.departmentBioscience Core Lab
dc.contributor.departmentKing Abdullah University of Science and Technology.
dc.identifier.journalG3 (Bethesda, Md.)
dc.eprint.versionPost-print
kaust.personFukasawa, Yoshinori
kaust.personErmini, Luca
kaust.personWang, Hai
kaust.personCarty, Karen
kaust.personCheung, Ming Sin
dc.date.accepted2020-02-01
refterms.dateFOA2020-02-13T11:04:01Z


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