Dataset Information

Colocalization analyses of genomic elements: approaches, recommendations and challenges.

ABSTRACT:

Motivation

Many high-throughput methods produce sets of genomic regions as one of their main outputs. Scientists often use genomic colocalization analysis to interpret such region sets, for example to identify interesting enrichments and to understand the interplay between the underlying biological processes. Although widely used, there is little standardization in how these analyses are performed. Different practices can substantially affect the conclusions of colocalization analyses.

Results

Here, we describe the different approaches and provide recommendations for performing genomic colocalization analysis, while also discussing common methodological challenges that may influence the conclusions. As illustrated by concrete example cases, careful attention to analysis details is needed in order to meet these challenges and to obtain a robust and biologically meaningful interpretation of genomic region set data.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Kanduri C

PROVIDER: S-EPMC6499241 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Colocalization analyses of genomic elements: approaches, recommendations and challenges.

Kanduri Chakravarthi C Bock Christoph C Gundersen Sveinung S Hovig Eivind E Sandve Geir Kjetil GK

Bioinformatics (Oxford, England) 20190501 9

<h4>Motivation</h4>Many high-throughput methods produce sets of genomic regions as one of their main outputs. Scientists often use genomic colocalization analysis to interpret such region sets, for example to identify interesting enrichments and to understand the interplay between the underlying biological processes. Although widely used, there is little standardization in how these analyses are performed. Different practices can substantially affect the conclusions of colocalization analyses.<h ...[more]

PMID: 30307532

Similar Datasets

Project description:BackgroundNext-generation sequencing techniques such as ChIP-seq allow researchers to investigate the genomic position of nuclear components and events. These experiments provide researchers with thousands of regions of interest to probe in order to identify biological relevance. As the cost of sequencing decreases and its robustness increases, more and more researchers turn to genome-wide studies to better understand the genomic elements they are studying. One way to interpret the output of sequencing studies is to investigate how the element of interest localizes in relationship to genome annotations and the binding of other nuclear components. Colocalization of genomic features could indicate cooperation and provide evidence for more detailed investigations. Although there are several existing tools for visualizing and analyzing colocalization, either they are difficult to use for experimental researchers, not well maintained, or without measurements for colocalization strength. Here we describe an online tool, ColoWeb, designed to allow experimentalists to compare their datasets to existing genomic features in order to generate hypotheses about biological interactions easily and quickly.ResultsColoWeb is a web-based service for evaluating the colocation of genomic features. Users submit genomic regions of interest, for example, a set of locations from a ChIP-seq analysis. ColoWeb compares the submitted regions of interest to the location of other genomic features such as transcription factors and chromatin modifiers. To facilitate comparisons among various genomic features, the output consists of both graphical representations and quantitative measures of the degree of colocalization between user's genomic regions and selected features. Frequent colocation may indicate a biological relationship.ConclusionColoWeb is a biologist-friendly web service that can quickly provide an assessment of thousands of genomic regions to identify colocated genomic features. ColoWeb is freely available at: http://projects.insilico.us.com/ColoWeb .

Dataset Information

Colocalization analyses of genomic elements: approaches, recommendations and challenges.

Motivation

Results

Supplementary information

Publications

Colocalization analyses of genomic elements: approaches, recommendations and challenges.

Similar Datasets

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