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dc.contributor.authorGonzález-Seoane, Borja
dc.contributor.authorPonte-Fernández, Christian
dc.contributor.authorGonzález-Domínguez, Jorge
dc.contributor.authorMartín, María J.
dc.date.accessioned2022-07-13T15:20:43Z
dc.date.available2022-07-13T15:20:43Z
dc.date.issued2022
dc.identifier.citationGonzález-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/s12859-022-04645-7es_ES
dc.identifier.urihttp://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.sponsorshipThis 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 manuscriptes_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2021/30es_ES
dc.language.isoenges_ES
dc.publisherBMCes_ES
dc.relation.urihttps://doi.org/10.1186/s12859-022-04645-7es_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectSimulationes_ES
dc.subjectEpistasis modeles_ES
dc.subjectGene interactiones_ES
dc.subjectPenetrancees_ES
dc.subjectPrevalencees_ES
dc.subjectHeritabilityes_ES
dc.subjectPythones_ES
dc.subjectSymPyes_ES
dc.titlePyToxo: a Python tool for calculating penetrance tables of high-order epistasis modelses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleBMC Bioinformaticses_ES
UDC.volume23es_ES
UDC.startPage117es_ES
dc.identifier.doi10.1186/s12859-022-04645-7


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