EXFI: Exon and splice graph prediction without a reference genome
dc.contributor.author | Langa Arranz, Jorge Eliseo | |
dc.contributor.author | Estomba Recalde, Miren Andone | |
dc.contributor.author | Conklin, Darrell | |
dc.date.accessioned | 2020-10-23T12:20:50Z | |
dc.date.available | 2020-10-23T12:20:50Z | |
dc.date.issued | 2020-08 | |
dc.identifier.citation | Ecology and Evolution 10(16) : 8880-8893 (2020) | es_ES |
dc.identifier.issn | 2045-7758 | |
dc.identifier.uri | http://hdl.handle.net/10810/47264 | |
dc.description.abstract | For 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.sponsorship | Basque Government, Grant/Award Number: predoctoral grant PRE_ 2017_2_0169 and grant IT558-10 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Wiley | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | exome sequencing | es_ES |
dc.subject | exon | es_ES |
dc.subject | sequence capture | es_ES |
dc.subject | SNP discovery | es_ES |
dc.subject | splice graph | es_ES |
dc.subject | transcriptome sequence | es_ES |
dc.subject | alignment | es_ES |
dc.subject | accurate | es_ES |
dc.subject | population | es_ES |
dc.subject | capture | es_ES |
dc.subject | tools | es_ES |
dc.subject | RAD | es_ES |
dc.title | EXFI: Exon and splice graph prediction without a reference genome | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | 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. | es_ES |
dc.rights.holder | Atribución 3.0 España | * |
dc.relation.publisherversion | https://onlinelibrary.wiley.com/doi/full/10.1002/ece3.6587 | es_ES |
dc.identifier.doi | 10.1002/ece3.6587 | |
dc.departamentoes | Ciencia de la computación e inteligencia artificial | es_ES |
dc.departamentoes | Genética, antropología física y fisiología animal | es_ES |
dc.departamentoeu | Genetika,antropologia fisikoa eta animalien fisiologia | es_ES |
dc.departamentoeu | Konputazio zientziak eta adimen artifiziala | es_ES |
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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.