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Nucleic Acids Res. 2018 Jul 2;46(W1):W186-W193. doi: 10.1093/nar/gky474.

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

Author information

1
Department of Informatics, University of Oslo, Gaustadalléen 23 B, N-0373 Oslo, Norway.
2
K. G. Jebsen Centre for Coeliac Disease Research, Oslo University Hospital, Sognsvannsveien 20, 0372 Oslo, Norway.
3
Elixir Norway - Oslo node, Department of Informatics, University of Oslo, Gaustadalléen 23 B, N-0373 Oslo, Norway.
4
CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria.
5
Department of Laboratory Medicine, Medical University of Vienna, 1090 Vienna, Austria.
6
Max Planck Institute for Informatics, 66123 Saarbrücken, Germany.
7
Cellular Genetics Programme, Wellcome Sanger Institute, CB10 1SA Hinxton, UK.
8
University of Pittsburgh School of Medicine, 3550 Terrace Street, Pittsburgh, PA 15213, USA.
9
Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, 550 N Broadway, Baltimore, MD 21205, USA.
10
Laboratory of Systems Biology and Computational Genetics, Vavilov Institute of General Genetics, Gubkina Street 3, Moscow 119333, Russia.
11
Department of Human Genetics, University of Utah, 15 N 2030 E, Salt Lake City, UT 84112, USA.
12
USTAR Center for Genetic Discovery, University of Utah, 15 N 2030 E, Salt Lake City, UT 84112, USA.
13
Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Lab. Bldg B, Vorobiovy Gory 1-73, Moscow 119992, Russia.
14
Skolkovo Institute of Science and Technology, Nobelya ul. 3, Moscow 121205, Russia.
15
Institute for Information Transmission Problems, Russian Academy of Sciences, Bolshoi Karenty per. 19, Moscow 127994, Russia.
16
Department of Biomedical Informatics, University of Utah, 421 Wakara Way, Salt Lake City, UT 84108, USA.
17
Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22903 USA.

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/.

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