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dc.contributor.authorda Fonseca, Rute R.
dc.contributor.authorAlbrechtsen, Anders
dc.contributor.authorEspregueira Themudo, Gonçalo
dc.contributor.authorRamos-Madrigal, Jazmín
dc.contributor.authorSibbesen, Jonas Andreas
dc.contributor.authorMaretty, Lasse
dc.contributor.authorZepeda-Mendoza, M. Lisandra
dc.contributor.authorCampos, Paula F.
dc.contributor.authorHeller, Rasmus
dc.contributor.authorPereira, Ricardo J.
dc.date.accessioned2019-08-09T21:45:42Z
dc.date.available2019-08-09T21:45:42Z
dc.date.issued2016
dc.identifier.citationda Fonseca, R.R.; Albrechtsen, A.; Espregueira Themudo, J.G.; Ramos-Madrigal, J.; Sibbesen, J.A.; Maretty, L.; Zepeda-Mendoza, M.L.; Campos, P.F.; Heller, R. and Pereira, R.J. (2016) Next-generation biology: Sequencing and data analysis approaches for non-model organisms. Marine Genomics, 6, pp.3-13. DOI: https://doi.org/10.1016/j.margen.2016.04.012.en_US
dc.identifier.urihttp://hdl.handle.net/11329/1012
dc.identifier.urihttp://dx.doi.org/10.25607/OBP-544
dc.description.abstractAs sequencing technologies become more affordable, it is now realistic to propose studying the evolutionary history of virtually any organism on a genomic scale. However, when dealing with non-model organisms it is not always easy to choose the best approach given a specific biological question, a limited budget, and challenging sample material. Furthermore, although recent advances in technology offer unprecedented opportunities for research in non-model organisms, they also demand unprecedented awareness from the researcher regarding the assumptions and limitations of each method.In this review we present an overview of the current sequencing technologies and the methods used in typical high-throughput data analysis pipelines. Subsequently,we contextualize high-throughput DNA sequencing technologies within their applications in non-model organism biology. We include tips regarding managing unconventional sample material, comparative and population genetic approaches that do not require fully assembled genomes, and advice on how to deal with low depth sequencing data.en_US
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.otherRADseqen_US
dc.subject.otherRNAseqen_US
dc.subject.otherTargeted sequencingen_US
dc.subject.otherGenotype likelihoodsen_US
dc.subject.otherComparative genomicsen_US
dc.subject.otherPopulation genomicen_US
dc.titleNext-generation biology: Sequencing and data analysis approaches fornon-model organisms.en_US
dc.typeJournal Contributionen_US
dc.description.refereedRefereeden_US
dc.format.pagerangepp.3-13en_US
dc.identifier.doihttps://doi.org/10.1016/j.margen.2016.04.012
dc.subject.parameterDisciplineParameter Discipline::Biological oceanography::Other biological measurementsen_US
dc.subject.dmProcessesData Management Practices::Data analysisen_US
dc.bibliographicCitation.titleMarine Genomicsen_US
dc.bibliographicCitation.volume6en_US
dc.description.sdg14en_US
dc.description.bptypeBest Practiceen_US
dc.description.bptypeGuideen_US
obps.contact.contactnameR.R. da Fonseca
obps.contact.contactemailfonseca@binf.ku.dk
obps.resourceurl.publisherhttps://www.sciencedirect.com/science/article/pii/S1874778716300368en_US


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International