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Coloc-stats: a unified web interface to perform colocalization analysis of genomic features
Functional genomics assays produce sets of genomic regions as one of their main outputs. To biologically interpret such region-sets, researchers often use colocalization analysis, where the statistical significance of colocalization (overlap, spatial proximity) between two or more region-sets is tes...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030976/ https://www.ncbi.nlm.nih.gov/pubmed/29873782 http://dx.doi.org/10.1093/nar/gky474 |
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author | Simovski, Boris Kanduri, Chakravarthi Gundersen, Sveinung Titov, Dmytro Domanska, Diana Bock, Christoph Bossini-Castillo, Lara Chikina, Maria Favorov, Alexander Layer, Ryan M Mironov, Andrey A Quinlan, Aaron R Sheffield, Nathan C Trynka, Gosia Sandve, Geir K |
author_facet | Simovski, Boris Kanduri, Chakravarthi Gundersen, Sveinung Titov, Dmytro Domanska, Diana Bock, Christoph Bossini-Castillo, Lara Chikina, Maria Favorov, Alexander Layer, Ryan M Mironov, Andrey A Quinlan, Aaron R Sheffield, Nathan C Trynka, Gosia Sandve, Geir K |
author_sort | Simovski, Boris |
collection | PubMed |
description | Functional genomics assays produce sets of genomic regions as one of their main outputs. To biologically interpret such region-sets, researchers often use colocalization analysis, where the statistical significance of colocalization (overlap, spatial proximity) between two or more region-sets is tested. Existing colocalization analysis tools vary in the statistical methodology and analysis approaches, thus potentially providing different conclusions for the same research question. As the findings of colocalization analysis are often the basis for follow-up experiments, it is helpful to use several tools in parallel and to compare the results. We developed the Coloc-stats web service to facilitate such analyses. Coloc-stats provides a unified interface to perform colocalization analysis across various analytical methods and method-specific options (e.g. colocalization measures, resolution, null models). Coloc-stats helps the user to find a method that supports their experimental requirements and allows for a straightforward comparison across methods. Coloc-stats is implemented as a web server with a graphical user interface that assists users with configuring their colocalization analyses. Coloc-stats is freely available at https://hyperbrowser.uio.no/coloc-stats/. |
format | Online Article Text |
id | pubmed-6030976 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60309762018-07-10 Coloc-stats: a unified web interface to perform colocalization analysis of genomic features Simovski, Boris Kanduri, Chakravarthi Gundersen, Sveinung Titov, Dmytro Domanska, Diana Bock, Christoph Bossini-Castillo, Lara Chikina, Maria Favorov, Alexander Layer, Ryan M Mironov, Andrey A Quinlan, Aaron R Sheffield, Nathan C Trynka, Gosia Sandve, Geir K Nucleic Acids Res Web Server Issue Functional genomics assays produce sets of genomic regions as one of their main outputs. To biologically interpret such region-sets, researchers often use colocalization analysis, where the statistical significance of colocalization (overlap, spatial proximity) between two or more region-sets is tested. Existing colocalization analysis tools vary in the statistical methodology and analysis approaches, thus potentially providing different conclusions for the same research question. As the findings of colocalization analysis are often the basis for follow-up experiments, it is helpful to use several tools in parallel and to compare the results. We developed the Coloc-stats web service to facilitate such analyses. Coloc-stats provides a unified interface to perform colocalization analysis across various analytical methods and method-specific options (e.g. colocalization measures, resolution, null models). Coloc-stats helps the user to find a method that supports their experimental requirements and allows for a straightforward comparison across methods. Coloc-stats is implemented as a web server with a graphical user interface that assists users with configuring their colocalization analyses. Coloc-stats is freely available at https://hyperbrowser.uio.no/coloc-stats/. Oxford University Press 2018-07-02 2018-06-05 /pmc/articles/PMC6030976/ /pubmed/29873782 http://dx.doi.org/10.1093/nar/gky474 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Web Server Issue Simovski, Boris Kanduri, Chakravarthi Gundersen, Sveinung Titov, Dmytro Domanska, Diana Bock, Christoph Bossini-Castillo, Lara Chikina, Maria Favorov, Alexander Layer, Ryan M Mironov, Andrey A Quinlan, Aaron R Sheffield, Nathan C Trynka, Gosia Sandve, Geir K Coloc-stats: a unified web interface to perform colocalization analysis of genomic features |
title | Coloc-stats: a unified web interface to perform colocalization analysis of genomic features |
title_full | Coloc-stats: a unified web interface to perform colocalization analysis of genomic features |
title_fullStr | Coloc-stats: a unified web interface to perform colocalization analysis of genomic features |
title_full_unstemmed | Coloc-stats: a unified web interface to perform colocalization analysis of genomic features |
title_short | Coloc-stats: a unified web interface to perform colocalization analysis of genomic features |
title_sort | coloc-stats: a unified web interface to perform colocalization analysis of genomic features |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030976/ https://www.ncbi.nlm.nih.gov/pubmed/29873782 http://dx.doi.org/10.1093/nar/gky474 |
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