z-logo
open-access-imgOpen Access
Coloc-stats: a unified web interface to perform colocalization analysis of genomic features
Author(s) -
Boris Simovski,
Chakravarthi Kanduri,
Sveinung Gundersen,
Dmytro Titov,
Diana Domańska,
Christoph Bock,
Lara BossiniCastillo,
Maria Chikina,
Alexander V. Favorov,
Ryan M. Layer,
Andrey A. Mironov,
Aaron R. Quinlan,
Nathan C. Sheffield,
Gosia Trynka,
Geir Kjetil Sandve
Publication year - 2018
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gky474
Subject(s) - colocalization , biology , interface (matter) , statistical hypothesis testing , computer science , computational biology , statistics , mathematics , neuroscience , pulmonary surfactant , biochemistry , gibbs isotherm
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/.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom