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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
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/.
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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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