Coloc-stats: A unified web interface to perform colocalization analysis of genomic features

Boris Simovski, Chakravarthi Kanduri, Sveinung Gundersen, Dmytro Titov, Diana Domanska, Christoph Bock, Lara Bossini-Castillo, Maria Chikina, Alexander Favorov, Ryan M. Layer, Andrey A. Mironov, Aaron R. Quinlan, Nathan C. Sheffield, Gosia Trynka, Geir K. Sandve

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

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/.

Original languageEnglish (US)
Pages (from-to)W186-W193
JournalNucleic acids research
Volume46
Issue numberW1
DOIs
StatePublished - Jul 2 2018

ASJC Scopus subject areas

  • Genetics

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