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regioneReloaded: evaluating the association of multiple genomic region sets
MOTIVATION: Next-generation sequencing methods continue improving the annotation of genomes in part by determining the distribution of features such as epigenetic marks. Evaluating and interpreting the association between genomic regions and their features has become a common and challenging analysi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10681856/ https://www.ncbi.nlm.nih.gov/pubmed/37988135 http://dx.doi.org/10.1093/bioinformatics/btad704 |
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author | Malinverni, Roberto Corujo, David Gel, Bernat Buschbeck, Marcus |
author_facet | Malinverni, Roberto Corujo, David Gel, Bernat Buschbeck, Marcus |
author_sort | Malinverni, Roberto |
collection | PubMed |
description | MOTIVATION: Next-generation sequencing methods continue improving the annotation of genomes in part by determining the distribution of features such as epigenetic marks. Evaluating and interpreting the association between genomic regions and their features has become a common and challenging analysis in genomic and epigenomic studies. RESULTS: With regioneR we provided an R package allowing to assess the statistical significance of pairwise associations between genomic region sets using permutation tests. We now present the R package regioneReloaded that builds upon regioneR’s statistical foundation and extends the functionality for the simultaneous analysis and visualization of the associations between multiple genomic region sets. Thus, we provide a novel discovery tool for the identification of significant associations that warrant to be tested for functional interdependence. AVAILABILITY AND IMPLEMENTATION: regioneReloaded is an R package released under an Artistic-2.0 License. The source code and documentation are freely available through Bioconductor: http://www.bioconductor.org/packages/regioneReloaded. |
format | Online Article Text |
id | pubmed-10681856 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-106818562023-11-30 regioneReloaded: evaluating the association of multiple genomic region sets Malinverni, Roberto Corujo, David Gel, Bernat Buschbeck, Marcus Bioinformatics Applications Note MOTIVATION: Next-generation sequencing methods continue improving the annotation of genomes in part by determining the distribution of features such as epigenetic marks. Evaluating and interpreting the association between genomic regions and their features has become a common and challenging analysis in genomic and epigenomic studies. RESULTS: With regioneR we provided an R package allowing to assess the statistical significance of pairwise associations between genomic region sets using permutation tests. We now present the R package regioneReloaded that builds upon regioneR’s statistical foundation and extends the functionality for the simultaneous analysis and visualization of the associations between multiple genomic region sets. Thus, we provide a novel discovery tool for the identification of significant associations that warrant to be tested for functional interdependence. AVAILABILITY AND IMPLEMENTATION: regioneReloaded is an R package released under an Artistic-2.0 License. The source code and documentation are freely available through Bioconductor: http://www.bioconductor.org/packages/regioneReloaded. Oxford University Press 2023-11-21 /pmc/articles/PMC10681856/ /pubmed/37988135 http://dx.doi.org/10.1093/bioinformatics/btad704 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Malinverni, Roberto Corujo, David Gel, Bernat Buschbeck, Marcus regioneReloaded: evaluating the association of multiple genomic region sets |
title | regioneReloaded: evaluating the association of multiple genomic region sets |
title_full | regioneReloaded: evaluating the association of multiple genomic region sets |
title_fullStr | regioneReloaded: evaluating the association of multiple genomic region sets |
title_full_unstemmed | regioneReloaded: evaluating the association of multiple genomic region sets |
title_short | regioneReloaded: evaluating the association of multiple genomic region sets |
title_sort | regionereloaded: evaluating the association of multiple genomic region sets |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10681856/ https://www.ncbi.nlm.nih.gov/pubmed/37988135 http://dx.doi.org/10.1093/bioinformatics/btad704 |
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