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PyToxo: a Python tool for calculating penetrance tables of high-order epistasis models
dc.contributor.author | González-Seoane, Borja | |
dc.contributor.author | Ponte-Fernández, Christian | |
dc.contributor.author | González-Domínguez, Jorge | |
dc.contributor.author | Martín, María J. | |
dc.date.accessioned | 2022-07-13T15:20:43Z | |
dc.date.available | 2022-07-13T15:20:43Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | González-Seoane, B., Ponte-Fernández, C., González-Domínguez, J. et al. PyToxo: a Python tool for calculating penetrance tables of high-order epistasis models. BMC Bioinformatics 23, 117 (2022). https://doi.org/10.1186/s12859-022-04645-7 | es_ES |
dc.identifier.uri | http://hdl.handle.net/2183/31178 | |
dc.description.abstract | [Abstract] Background Epistasis is the interaction between different genes when expressing a certain phenotype. If epistasis involves more than two loci it is called high-order epistasis. High-order epistasis is an area under active research because it could be the cause of many complex traits. The most common way to specify an epistasis interaction is through a penetrance table. Results This paper presents PyToxo, a Python tool for generating penetrance tables from any-order epistasis models. Unlike other tools available in the bibliography, PyToxo is able to work with high-order models and realistic penetrance and heritability values, achieving high-precision results in a short time. In addition, PyToxo is distributed as open-source software and includes several interfaces to ease its use. Conclusions PyToxo provides the scientific community with a useful tool to evaluate algorithms and methods that can detect high-order epistasis to continue advancing in the discovery of the causes behind complex diseases. | es_ES |
dc.description.sponsorship | This study and publication costs were funded by the Ministry of Science and Innovation of Spain (grant PID2019-104184RB-I00/AEI/10.13039/501100011033) and by Xunta de Galicia and FEDER funds of the EU (CITIC-Centro de Investigación de Galicia accreditation, grant ED431G 2019/01; Consolidation Program of Competitive Reference Groups, grant ED431C 2021/30). CP was funded by the Ministry of Education of Spain (grant FPU16/01333). The funders did not play any role in the design of the study, the collection, analysis, and interpretation of data, or in writing of the manuscript | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2021/30 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | BMC | es_ES |
dc.relation.uri | https://doi.org/10.1186/s12859-022-04645-7 | es_ES |
dc.rights | Atribución 3.0 España | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Simulation | es_ES |
dc.subject | Epistasis model | es_ES |
dc.subject | Gene interaction | es_ES |
dc.subject | Penetrance | es_ES |
dc.subject | Prevalence | es_ES |
dc.subject | Heritability | es_ES |
dc.subject | Python | es_ES |
dc.subject | SymPy | es_ES |
dc.title | PyToxo: a Python tool for calculating penetrance tables of high-order epistasis models | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | BMC Bioinformatics | es_ES |
UDC.volume | 23 | es_ES |
UDC.startPage | 117 | es_ES |
dc.identifier.doi | 10.1186/s12859-022-04645-7 |
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