EvolSOM: An R Package for evolutionary conservation analysis with SOMs

Autores
Prochetto, Santiago; Reinheimer, Renata; Stegmayer, Georgina
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Motivation: Unraveling the connection between genes and traits is crucial for solving many biological puzzles. In the intricate structure of DNA, genes provide instructions for building cellular machinery, directing the processes that sustain life. RNA molecules and proteins, derived from these genetic instructions, play crucial roles in shaping cell structures, influencing reactions, and guiding behavior. This fundamental biological principle links genetic makeup to observable traits, but integrating and extracting meaningful relationships from this complex, multimodal data presents a significant challenge. Results: We introduce evolSOM, a novel R package that utilizes Self-Organizing Maps (SOMs) to explore and visualize the conservation of biological variables, easing the integration of phenotypic and genotypic attributes. The package enables the projection of multi-dimensional expression profiles onto easily interpretable two-dimensional grids, aiding in the identification of conserved gene modules/phenotypes across multiple species or conditions. By constructing species-specific or condition-specific SOMs that capture non-redundant patterns, evolSOM allows the analysis of displacement of biological variables between species or conditions. Variables displaced together suggest membership in the same regulatory network, and the nature of the displacement (early/delayed/flip) may hold biological significance. These displacements are automatically calculated and graphically presented by the package, enabling efficient comparison and revealing both conserved and displaced variables. The package facilitates the integration of diverse phenotypic data types, such as morphological data or metabolomics, enabling the exploration of potential gene drivers underlying observed phenotypic changes. Its user-friendly interface and visualization capabilities enhance the accessibility of complex network analyses. As an illustrative example, we employed evolSOM to study the displacement of genes and phenotypic traits, successfully identifying potential drivers of phenotypic differentiation in grass leaves.
Fil: Prochetto, Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Agrobiotecnología del Litoral. Universidad Nacional del Litoral. Instituto de Agrobiotecnología del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Fil: Reinheimer, Renata. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Agrobiotecnología del Litoral. Universidad Nacional del Litoral. Instituto de Agrobiotecnología del Litoral; Argentina
Fil: Stegmayer, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Materia
Conservation
SOM
Phenotipe
Genes
Evolution
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/263045
Acceder
id CONICETDig_92058fdd23cc10c797770331facf374f
oai_identifier_str oai:ri.conicet.gov.ar:11336/263045
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling EvolSOM: An R Package for evolutionary conservation analysis with SOMsProchetto, SantiagoReinheimer, RenataStegmayer, GeorginaConservationSOMPhenotipeGenesEvolutionhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Motivation: Unraveling the connection between genes and traits is crucial for solving many biological puzzles. In the intricate structure of DNA, genes provide instructions for building cellular machinery, directing the processes that sustain life. RNA molecules and proteins, derived from these genetic instructions, play crucial roles in shaping cell structures, influencing reactions, and guiding behavior. This fundamental biological principle links genetic makeup to observable traits, but integrating and extracting meaningful relationships from this complex, multimodal data presents a significant challenge. Results: We introduce evolSOM, a novel R package that utilizes Self-Organizing Maps (SOMs) to explore and visualize the conservation of biological variables, easing the integration of phenotypic and genotypic attributes. The package enables the projection of multi-dimensional expression profiles onto easily interpretable two-dimensional grids, aiding in the identification of conserved gene modules/phenotypes across multiple species or conditions. By constructing species-specific or condition-specific SOMs that capture non-redundant patterns, evolSOM allows the analysis of displacement of biological variables between species or conditions. Variables displaced together suggest membership in the same regulatory network, and the nature of the displacement (early/delayed/flip) may hold biological significance. These displacements are automatically calculated and graphically presented by the package, enabling efficient comparison and revealing both conserved and displaced variables. The package facilitates the integration of diverse phenotypic data types, such as morphological data or metabolomics, enabling the exploration of potential gene drivers underlying observed phenotypic changes. Its user-friendly interface and visualization capabilities enhance the accessibility of complex network analyses. As an illustrative example, we employed evolSOM to study the displacement of genes and phenotypic traits, successfully identifying potential drivers of phenotypic differentiation in grass leaves.Fil: Prochetto, Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Agrobiotecnología del Litoral. Universidad Nacional del Litoral. Instituto de Agrobiotecnología del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Reinheimer, Renata. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Agrobiotecnología del Litoral. Universidad Nacional del Litoral. Instituto de Agrobiotecnología del Litoral; ArgentinaFil: Stegmayer, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaCornell University2024-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/263045Prochetto, Santiago; Reinheimer, Renata; Stegmayer, Georgina; EvolSOM: An R Package for evolutionary conservation analysis with SOMs; Cornell University; arxiv; 2-2024; 1-82331-8422CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.48550/arXiv.2402.07948info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/2402.07948info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:39:53Zoai:ri.conicet.gov.ar:11336/263045instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:39:53.67CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv EvolSOM: An R Package for evolutionary conservation analysis with SOMs
title EvolSOM: An R Package for evolutionary conservation analysis with SOMs
spellingShingle EvolSOM: An R Package for evolutionary conservation analysis with SOMs
Prochetto, Santiago
Conservation
SOM
Phenotipe
Genes
Evolution
title_short EvolSOM: An R Package for evolutionary conservation analysis with SOMs
title_full EvolSOM: An R Package for evolutionary conservation analysis with SOMs
title_fullStr EvolSOM: An R Package for evolutionary conservation analysis with SOMs
title_full_unstemmed EvolSOM: An R Package for evolutionary conservation analysis with SOMs
title_sort EvolSOM: An R Package for evolutionary conservation analysis with SOMs
dc.creator.none.fl_str_mv Prochetto, Santiago
Reinheimer, Renata
Stegmayer, Georgina
author Prochetto, Santiago
author_facet Prochetto, Santiago
Reinheimer, Renata
Stegmayer, Georgina
author_role author
author2 Reinheimer, Renata
Stegmayer, Georgina
author2_role author
author
dc.subject.none.fl_str_mv Conservation
SOM
Phenotipe
Genes
Evolution
topic Conservation
SOM
Phenotipe
Genes
Evolution
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Motivation: Unraveling the connection between genes and traits is crucial for solving many biological puzzles. In the intricate structure of DNA, genes provide instructions for building cellular machinery, directing the processes that sustain life. RNA molecules and proteins, derived from these genetic instructions, play crucial roles in shaping cell structures, influencing reactions, and guiding behavior. This fundamental biological principle links genetic makeup to observable traits, but integrating and extracting meaningful relationships from this complex, multimodal data presents a significant challenge. Results: We introduce evolSOM, a novel R package that utilizes Self-Organizing Maps (SOMs) to explore and visualize the conservation of biological variables, easing the integration of phenotypic and genotypic attributes. The package enables the projection of multi-dimensional expression profiles onto easily interpretable two-dimensional grids, aiding in the identification of conserved gene modules/phenotypes across multiple species or conditions. By constructing species-specific or condition-specific SOMs that capture non-redundant patterns, evolSOM allows the analysis of displacement of biological variables between species or conditions. Variables displaced together suggest membership in the same regulatory network, and the nature of the displacement (early/delayed/flip) may hold biological significance. These displacements are automatically calculated and graphically presented by the package, enabling efficient comparison and revealing both conserved and displaced variables. The package facilitates the integration of diverse phenotypic data types, such as morphological data or metabolomics, enabling the exploration of potential gene drivers underlying observed phenotypic changes. Its user-friendly interface and visualization capabilities enhance the accessibility of complex network analyses. As an illustrative example, we employed evolSOM to study the displacement of genes and phenotypic traits, successfully identifying potential drivers of phenotypic differentiation in grass leaves.
Fil: Prochetto, Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Agrobiotecnología del Litoral. Universidad Nacional del Litoral. Instituto de Agrobiotecnología del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Fil: Reinheimer, Renata. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Agrobiotecnología del Litoral. Universidad Nacional del Litoral. Instituto de Agrobiotecnología del Litoral; Argentina
Fil: Stegmayer, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
description Motivation: Unraveling the connection between genes and traits is crucial for solving many biological puzzles. In the intricate structure of DNA, genes provide instructions for building cellular machinery, directing the processes that sustain life. RNA molecules and proteins, derived from these genetic instructions, play crucial roles in shaping cell structures, influencing reactions, and guiding behavior. This fundamental biological principle links genetic makeup to observable traits, but integrating and extracting meaningful relationships from this complex, multimodal data presents a significant challenge. Results: We introduce evolSOM, a novel R package that utilizes Self-Organizing Maps (SOMs) to explore and visualize the conservation of biological variables, easing the integration of phenotypic and genotypic attributes. The package enables the projection of multi-dimensional expression profiles onto easily interpretable two-dimensional grids, aiding in the identification of conserved gene modules/phenotypes across multiple species or conditions. By constructing species-specific or condition-specific SOMs that capture non-redundant patterns, evolSOM allows the analysis of displacement of biological variables between species or conditions. Variables displaced together suggest membership in the same regulatory network, and the nature of the displacement (early/delayed/flip) may hold biological significance. These displacements are automatically calculated and graphically presented by the package, enabling efficient comparison and revealing both conserved and displaced variables. The package facilitates the integration of diverse phenotypic data types, such as morphological data or metabolomics, enabling the exploration of potential gene drivers underlying observed phenotypic changes. Its user-friendly interface and visualization capabilities enhance the accessibility of complex network analyses. As an illustrative example, we employed evolSOM to study the displacement of genes and phenotypic traits, successfully identifying potential drivers of phenotypic differentiation in grass leaves.
publishDate 2024
dc.date.none.fl_str_mv 2024-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/263045
Prochetto, Santiago; Reinheimer, Renata; Stegmayer, Georgina; EvolSOM: An R Package for evolutionary conservation analysis with SOMs; Cornell University; arxiv; 2-2024; 1-8
2331-8422
CONICET Digital
CONICET
url http://hdl.handle.net/11336/263045
identifier_str_mv Prochetto, Santiago; Reinheimer, Renata; Stegmayer, Georgina; EvolSOM: An R Package for evolutionary conservation analysis with SOMs; Cornell University; arxiv; 2-2024; 1-8
2331-8422
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.48550/arXiv.2402.07948
info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/2402.07948
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Cornell University
publisher.none.fl_str_mv Cornell University
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844614425416302592
score 13.070432

Publicaciones similares