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dc.contributor.authorLanga Arranz, Jorge Eliseo ORCID
dc.contributor.authorEstomba Recalde, Miren Andone ORCID
dc.contributor.authorConklin, Darrell
dc.date.accessioned2020-10-23T12:20:50Z
dc.date.available2020-10-23T12:20:50Z
dc.date.issued2020-08
dc.identifier.citationEcology and Evolution 10(16) : 8880-8893 (2020)es_ES
dc.identifier.issn2045-7758
dc.identifier.urihttp://hdl.handle.net/10810/47264
dc.description.abstractFor population genetic studies in nonmodel organisms, it is important to use every single source of genomic information. This paper presents EXFI, a Python pipeline that predicts the splice graph and exon sequences using an assembled transcriptome and raw whole-genome sequencing reads. The main algorithm uses Bloom filters to remove reads that are not part of the transcriptome, to predict the intron-exon boundaries, to then proceed to call exons from the assembly, and to generate the underlying splice graph. The results are returned in GFA1 format, which encodes both the predicted exon sequences and how they are connected to form transcripts.es_ES
dc.description.sponsorshipBasque Government, Grant/Award Number: predoctoral grant PRE_ 2017_2_0169 and grant IT558-10es_ES
dc.language.isoenges_ES
dc.publisherWileyes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectexome sequencinges_ES
dc.subjectexones_ES
dc.subjectsequence capturees_ES
dc.subjectSNP discoveryes_ES
dc.subjectsplice graphes_ES
dc.subjecttranscriptome sequencees_ES
dc.subjectalignmentes_ES
dc.subjectaccuratees_ES
dc.subjectpopulationes_ES
dc.subjectcapturees_ES
dc.subjecttoolses_ES
dc.subjectRADes_ES
dc.titleEXFI: Exon and splice graph prediction without a reference genomees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.es_ES
dc.rights.holderAtribución 3.0 España*
dc.relation.publisherversionhttps://onlinelibrary.wiley.com/doi/full/10.1002/ece3.6587es_ES
dc.identifier.doi10.1002/ece3.6587
dc.departamentoesCiencia de la computación e inteligencia artificiales_ES
dc.departamentoesGenética, antropología física y fisiología animales_ES
dc.departamentoeuGenetika,antropologia fisikoa eta animalien fisiologiaes_ES
dc.departamentoeuKonputazio zientziak eta adimen artifizialaes_ES


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2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.