Differential splicing analysis based on isoforms expression with NBSplice

Autores
Merino, Gabriela Alejandra; Fernandez, Elmer Andres
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Alternative splicing alterations have been widely related to several human diseases revealing the importance of their study for the success of translational medicine. Differential splicing (DS) occurrence has been mainly analyzed through exon-based approaches over RNA-seq data. Although these strategies allow identifying differentially spliced genes, they ignore the identity of the affected gene isoforms which is crucial to understand the underlying pathological processes behind alternative splicing changes. Moreover, despite several isoform quantification tools for RNA-seq data have been recently developed, DS tools have not taken advantage of them. Here, the NBSplice R package for differential splicing analysis by means of isoform expression data is presented. It estimates differences on relative expressions of gene transcripts between experimental conditions to infer changes in gene alternative splicing patterns. The developed tool was evaluated using a synthetic RNA-seq dataset with controlled differential splicing. NBSplice accurately predicted DS occurrence, outperforming current methods in terms of accuracy, sensitivity, F-score, and false discovery rate control. The usefulness of our development was demonstrated by the analysis of a real cancer dataset, revealing new differentially spliced genes that could be studied pursuing new colorectal cancer biomarkers discovery.
Fil: Merino, Gabriela Alejandra. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; Argentina
Fil: Fernandez, Elmer Andres. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigación y Desarrollo en Inmunología y Enfermedades Infecciosas. Universidad Católica de Córdoba. Centro de Investigación y Desarrollo en Inmunología y Enfermedades Infecciosas; Argentina
Materia
TRANSCRIPTOMICS
RNA-SEQ
ALTERNATIVE SPLICING
CANCER
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/106730
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/106730
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Differential splicing analysis based on isoforms expression with NBSpliceMerino, Gabriela AlejandraFernandez, Elmer AndresTRANSCRIPTOMICSRNA-SEQALTERNATIVE SPLICINGCANCERhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Alternative splicing alterations have been widely related to several human diseases revealing the importance of their study for the success of translational medicine. Differential splicing (DS) occurrence has been mainly analyzed through exon-based approaches over RNA-seq data. Although these strategies allow identifying differentially spliced genes, they ignore the identity of the affected gene isoforms which is crucial to understand the underlying pathological processes behind alternative splicing changes. Moreover, despite several isoform quantification tools for RNA-seq data have been recently developed, DS tools have not taken advantage of them. Here, the NBSplice R package for differential splicing analysis by means of isoform expression data is presented. It estimates differences on relative expressions of gene transcripts between experimental conditions to infer changes in gene alternative splicing patterns. The developed tool was evaluated using a synthetic RNA-seq dataset with controlled differential splicing. NBSplice accurately predicted DS occurrence, outperforming current methods in terms of accuracy, sensitivity, F-score, and false discovery rate control. The usefulness of our development was demonstrated by the analysis of a real cancer dataset, revealing new differentially spliced genes that could be studied pursuing new colorectal cancer biomarkers discovery.Fil: Merino, Gabriela Alejandra. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; ArgentinaFil: Fernandez, Elmer Andres. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigación y Desarrollo en Inmunología y Enfermedades Infecciosas. Universidad Católica de Córdoba. Centro de Investigación y Desarrollo en Inmunología y Enfermedades Infecciosas; ArgentinaAcademic Press Inc Elsevier Science2020-03info: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/11336/106730Merino, Gabriela Alejandra; Fernandez, Elmer Andres; Differential splicing analysis based on isoforms expression with NBSplice; Academic Press Inc Elsevier Science; Journal Of Biomedical Informatics; 103; 3-2020; 103378-1/111532-0464CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S1532046420300058info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jbi.2020.103378info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:06:39Zoai:ri.conicet.gov.ar:11336/106730instacron: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 10:06:39.59CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Differential splicing analysis based on isoforms expression with NBSplice
title Differential splicing analysis based on isoforms expression with NBSplice
spellingShingle Differential splicing analysis based on isoforms expression with NBSplice
Merino, Gabriela Alejandra
TRANSCRIPTOMICS
RNA-SEQ
ALTERNATIVE SPLICING
CANCER
title_short Differential splicing analysis based on isoforms expression with NBSplice
title_full Differential splicing analysis based on isoforms expression with NBSplice
title_fullStr Differential splicing analysis based on isoforms expression with NBSplice
title_full_unstemmed Differential splicing analysis based on isoforms expression with NBSplice
title_sort Differential splicing analysis based on isoforms expression with NBSplice
dc.creator.none.fl_str_mv Merino, Gabriela Alejandra
Fernandez, Elmer Andres
author Merino, Gabriela Alejandra
author_facet Merino, Gabriela Alejandra
Fernandez, Elmer Andres
author_role author
author2 Fernandez, Elmer Andres
author2_role author
dc.subject.none.fl_str_mv TRANSCRIPTOMICS
RNA-SEQ
ALTERNATIVE SPLICING
CANCER
topic TRANSCRIPTOMICS
RNA-SEQ
ALTERNATIVE SPLICING
CANCER
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Alternative splicing alterations have been widely related to several human diseases revealing the importance of their study for the success of translational medicine. Differential splicing (DS) occurrence has been mainly analyzed through exon-based approaches over RNA-seq data. Although these strategies allow identifying differentially spliced genes, they ignore the identity of the affected gene isoforms which is crucial to understand the underlying pathological processes behind alternative splicing changes. Moreover, despite several isoform quantification tools for RNA-seq data have been recently developed, DS tools have not taken advantage of them. Here, the NBSplice R package for differential splicing analysis by means of isoform expression data is presented. It estimates differences on relative expressions of gene transcripts between experimental conditions to infer changes in gene alternative splicing patterns. The developed tool was evaluated using a synthetic RNA-seq dataset with controlled differential splicing. NBSplice accurately predicted DS occurrence, outperforming current methods in terms of accuracy, sensitivity, F-score, and false discovery rate control. The usefulness of our development was demonstrated by the analysis of a real cancer dataset, revealing new differentially spliced genes that could be studied pursuing new colorectal cancer biomarkers discovery.
Fil: Merino, Gabriela Alejandra. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; Argentina
Fil: Fernandez, Elmer Andres. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigación y Desarrollo en Inmunología y Enfermedades Infecciosas. Universidad Católica de Córdoba. Centro de Investigación y Desarrollo en Inmunología y Enfermedades Infecciosas; Argentina
description Alternative splicing alterations have been widely related to several human diseases revealing the importance of their study for the success of translational medicine. Differential splicing (DS) occurrence has been mainly analyzed through exon-based approaches over RNA-seq data. Although these strategies allow identifying differentially spliced genes, they ignore the identity of the affected gene isoforms which is crucial to understand the underlying pathological processes behind alternative splicing changes. Moreover, despite several isoform quantification tools for RNA-seq data have been recently developed, DS tools have not taken advantage of them. Here, the NBSplice R package for differential splicing analysis by means of isoform expression data is presented. It estimates differences on relative expressions of gene transcripts between experimental conditions to infer changes in gene alternative splicing patterns. The developed tool was evaluated using a synthetic RNA-seq dataset with controlled differential splicing. NBSplice accurately predicted DS occurrence, outperforming current methods in terms of accuracy, sensitivity, F-score, and false discovery rate control. The usefulness of our development was demonstrated by the analysis of a real cancer dataset, revealing new differentially spliced genes that could be studied pursuing new colorectal cancer biomarkers discovery.
publishDate 2020
dc.date.none.fl_str_mv 2020-03
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/11336/106730
Merino, Gabriela Alejandra; Fernandez, Elmer Andres; Differential splicing analysis based on isoforms expression with NBSplice; Academic Press Inc Elsevier Science; Journal Of Biomedical Informatics; 103; 3-2020; 103378-1/11
1532-0464
CONICET Digital
CONICET
url http://hdl.handle.net/11336/106730
identifier_str_mv Merino, Gabriela Alejandra; Fernandez, Elmer Andres; Differential splicing analysis based on isoforms expression with NBSplice; Academic Press Inc Elsevier Science; Journal Of Biomedical Informatics; 103; 3-2020; 103378-1/11
1532-0464
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S1532046420300058
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jbi.2020.103378
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Academic Press Inc Elsevier Science
publisher.none.fl_str_mv Academic Press Inc Elsevier Science
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
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score 13.070432

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