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acorde unravels functionally interpretable networks of isoform co-usage from single cell data

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acorde unravels functionally interpretable networks of isoform co-usage from single cell data

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dc.contributor.author Arzalluz-Luque, Ángeles es_ES
dc.contributor.author Salguero-García, Pedro es_ES
dc.contributor.author Tarazona, Sonia es_ES
dc.contributor.author Conesa, Ana es_ES
dc.date.accessioned 2023-03-29T18:01:04Z
dc.date.available 2023-03-29T18:01:04Z
dc.date.issued 2022-04-05 es_ES
dc.identifier.issn 2041-1723 es_ES
dc.identifier.uri http://hdl.handle.net/10251/192651
dc.description.abstract [EN] Alternative splicing (AS) is a highly-regulated post-transcriptional mechanism known to modulate isoform expression within genes and contribute to cell-type identity. However, the extent to which alternative isoforms establish co-expression networks that may be relevant in cellular function has not been explored yet. Here, we present acorde, a pipeline that successfully leverages bulk long reads and single-cell data to confidently detect alternative isoform co-expression relationships. To achieve this, we develop and validate percentile correlations, an innovative approach that overcomes data sparsity and yields accurate coexpression estimates from single-cell data. Next, acorde uses correlations to cluster coexpressed isoforms into a network, unraveling cell type-specific alternative isoform usage patterns. By selecting same-gene isoforms between these clusters, we subsequently detect and characterize genes with co-differential isoform usage (coDIU) across cell types. Finally, we predict functional elements from long read-defined isoforms and provide insight into biological processes, motifs, and domains potentially controlled by the coordination of post-transcriptional regulation. The code for acorde is available at https://github.com/ConesaLab/acorde. es_ES
dc.description.sponsorship This work has been funded by NIH grant R21HG011280 (A.C.) and by the Spanish Ministry of Science grants BIO2015-1658-R (A.C., S.T.), BES-2016-076994 (A.A.L.) and PID2020-119537RB-100 (A.C., S.T.). Funding for open access charge provided by the Universitat Politecnica de Valencia and the Spanish Ministry of Science grant PID2020-119537RB-100. es_ES
dc.language Inglés es_ES
dc.publisher Nature Publishing Group es_ES
dc.relation.ispartof Nature Communications es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title acorde unravels functionally interpretable networks of isoform co-usage from single cell data es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1038/s41467-022-29497-w es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-119537RB-I00/ES/INTEGRACION DE DATOS MULTI-OMICOS PARA LA INFERENCIA DE MODELOS MULTI-CAPA DE ENFERMEDAD/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NIH//R21HG011280/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//BIO2015-1658-R/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//BES-2016-076994/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica es_ES
dc.description.bibliographicCitation Arzalluz-Luque, Á.; Salguero-García, P.; Tarazona, S.; Conesa, A. (2022). acorde unravels functionally interpretable networks of isoform co-usage from single cell data. Nature Communications. 13(1):1-18. https://doi.org/10.1038/s41467-022-29497-w es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1038/s41467-022-29497-w es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 18 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 13 es_ES
dc.description.issue 1 es_ES
dc.identifier.pmid 35383181 es_ES
dc.identifier.pmcid PMC8983708 es_ES
dc.relation.pasarela S\463249 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder National Institutes of Health, EEUU es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
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