Category Genomics>Gene Expression Analysis/Profiling/Tools and Cross-Omics>Pathway Analysis/Gene Regulatory Networks/Tools

Abstract ClueGO is an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes.

ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta Pathways and creates a functionally organized GO/pathway term network.

It can analyze one or compare two (2) lists of genes and comprehensively visualizes functionally grouped terms.

ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in (see below...).

The (gene) identifiers can be uploaded from a text file or interactively from a network of Cytoscape. The type of identifiers supported can be easily extended by the user.

ClueGO performs single cluster analysis and comparison of clusters. From the ontology sources used, the terms are selected by different filter criteria. The related terms which share similar associated genes, can be fused to reduce redundancy.

The ClueGO network is created with kappa statistics and reflects the relationships between the terms based on the similarity of their associated genes.

On the network, the node color can be switched between functional groups and clusters distribution. ClueGO charts underlie the specificity and the common aspects of the biological role. The significance of the terms and groups is automatically calculated.

A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time.

GOlorize plug-in --

GOlorize provides class-guided network visualization in Cytoscape. GOlorize uses Gene Ontology (GO) categories or other additional class information to direct the network graph layout process and to emphasize the biological function of the nodes.

It can be used in conjunction with the BiNGO (A Biological Network Gene Ontology tool), an efficient tool to find the GO categories that are overrepresented in a selected part of the network.

GOlorize first highlights the nodes that belong to the same class using color-coding and then constructs an enhanced visualization of the network using a class-directed layout algorithm.

ClueGO features/capabilities include:

1) ClueGO allows the analysis of a single gene set (cluster) or cluster comparison.

2) Different filter criteria can be applied to the terms.

3) Fusion of the related terms that have similar associated genes.

4) Functional grouping of the terms based on GO hierarchy or based on kappa score.

5) Visualization of the selected terms in a functionally grouped network.

6) Charts presenting the specific terms and groups for the clusters compared.

7) Statistical significance for the terms and for the groups.

8) ClueGO can be used in combination with GOlorize (as stated above...).

9) ClueGO is easily updatable.

10) ClueGO is also easily extendable.

Note: ClueGO has two (2) major features: it can be either used for the visualization of terms corresponding to a list of genes, or the comparison of functional annotations of two (2) clusters.

ClueGO Data import --

Gene identifier sets can be directly uploaded in a simple text format or interactively derived from the gene network graphs visualized in Cytoscape.

ClueGO supports several gene identifiers and organisms by default and is extendable for additional ones in a plug-in like manner.

ClueGO Enrichment tests --

ClueGO offers the possibility to calculate enrichment/depletion tests for terms and groups as left-sided (Enrichment), right-sided (Depletion) or two-sided (Enrichment/Depletion) tests based on hypergeometric distribution.

Furthermore, it provides options to calculate mid-P-values and doubling for two-sided tests to deal with discreetness and conservatism effects.

To correct the P-values for multiple testing, several standard correction methods are provided (Bonferroni, Bonferroni step-down, and Benjamini-Hochberg).

ClueGO Network generation and visualization --

To create the annotations network ClueGO provides predefined functional analysis settings ranging from general to very specific ones. Furthermore, the user can adjust the analysis parameters to focus on terms, e.g. in certain GO level intervals, with particular evidence codes or with a certain number and percentage of associated genes.

An optional redundancy reduction feature (Fusion) assesses GO terms in a parent-child relation sharing similar associated genes and preserves the more representative parent or child term. The relationship between the selected terms is defined based on their shared genes.

ClueGO first creates a binary gene-term matrix with the selected terms and their associated genes. Based on this matrix, a term-term similarity matrix is calculated using chance corrected kappa statistics to determine the association strength between the terms.

Finally, the created network represents the terms as nodes which are linked based on a predefined kappa score level. The kappa score level threshold can be initially adjusted on a positive scale from 0 to 1 to restrict the network connectivity in a customized way.

The size of the nodes reflects the enrichment significance of the terms. The network is automatically laid out using the Organic layout algorithm supported by Cytoscape.

The functional groups are created by iterative merging of initially defined groups based on the predefined kappa score threshold.

The final groups are fixed or randomly colored and overlaid with the network. Functional groups represented by their most significant (leading) term are visualized in the network providing an insightful view of their interrelations.

Also other ways of selecting the groups leading term, e.g. based on the number or percentage of genes per term, are provided.

As an alternative to the kappa score grouping the GO hierarchy, using parent-child relationships can be used to create functional groups.

When comparing two gene clusters, another original feature of ClueGO, allows you to switch the visualization of the groups on the network to the cluster distribution over the terms.

Besides the network, ClueGO provides overview charts showing the groups and their leading terms as well as detailed term histograms for both, cluster specific and common terms.

The created networks, charts, and analysis results can also be saved as a project in a specified folder and used for further analysis.

System Requirements

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Manufacturer Web Site ClueGO

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G6G Abstract Number 20734

G6G Manufacturer Number 101146