GO Tools: Visualization

Gene Ontology (GO), the de facto standard in gene functionality description, is used widely in functional annotation and enrichment analysis. Here, we introduce agriGO, an integrated web-based GO analysis toolkit for the agricultural community, using the advantages of our previous GO enrichment tool (EasyGO), to meet analysis demands from new technologies and research objectives. EasyGO is valuable for its proficiency, and has proved useful in uncovering biological knowledge in massive data sets from high-throughput experiments. For agriGO, the system architecture and website interface were redesigned to improve performance and accessibility. The supported organisms and gene identifiers were substantially expanded (including 38 agricultural species composed of 274 data types). The requirement on user input is more flexible, in that user-defined reference and annotation are accepted. Moreover, a new analysis approach using Gene Set Enrichment Analysis strategy and customizable features is provided. Four tools, SEA (Singular enrichment analysis), PAGE (Parametric Analysis of Gene set Enrichment), BLAST4ID (Transfer IDs by BLAST) and SEACOMPARE (Cross comparison of SEA), are integrated as a toolkit to meet different demands. We also provide a cross-comparison service so that different data sets can be compared and explored in a visualized way. Lastly, agriGO functions as a GO data repository with search and download functions; agriGO is publicly accessible at http://bioinfo.cau.edu.cn/agriGO/.

• ontology or annotation browser
• ontology or annotation visualization
• database or data warehouse
• statistical analysis
• term enrichment
• text mining

AmiGO provides an interface to search and browse the ontology and annotation data provided by the GO consortium. Users can search for gene products and view the terms with which they are associated; alternatively, users can search or browse the ontology for GO terms of interest and see term details and gene product annotations. AmiGO also provides a BLAST search engine, which searches the sequences of genes and gene products that have been annotated to a GO term and submitted to the GO Consortium.

AmiGO accesses the GO mySQL database; more information is available from the GO database guide.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• slimmer-type tool
• term enrichment
• other analysis

Bioconductor provides tools for the analysis and comprehension of high-throughput (microarray, sequence, flow, etc.) genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. There are more than core and user-contributed 400 packages. Bioconductor packages the GO ontology into our semi-annual release, with software tools to: query; join with diverse additional gene, microarray, and sequence annotations; incorporate GO into annotation, differential expression, and gene set enrichment work flows; and visualize.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• software library
• statistical analysis
• term enrichment
• text mining
• other analysis
• Flexible integration of GO into statistical analysis and comprehension of high-throughput genetic data.

g:Profiler is a public web server for characterising and manipulating gene lists from high-throughput genomic data. g:Profiler has a simple user-friendly web interface with powerful visualisation. g:Profiler currently supports 85 species, including mammals, fungi, plants, insects, etc, from the Ensembl and Ensembl Genomes databases. g:Profiler consists of the following tools:

• g:GOSt retrieves most significant Gene Ontology (GO) terms, KEGG and REACTOME pathways, and TRANSFAC motifs to a user-specified group of genes, proteins or microarray probes. g:GOSt also allows analysis of ranked or ordered lists of genes, visual browsing of GO graph structure, interactive visualisation of retrieved results, and many other features. Multiple testing corrections are applied to extract only statistically important results.
• g:Convert allows conversion between gene or protein names, database IDs and microarray probes of more than 100 types. A mix of various IDs may be presented as input; output options include HTML, text and XLS spreadsheet.
• g:Orth retrieves orthologs for a given set of genes, proteins or probes in a selected organism. Graphical representation also shows orthologs present in all g:Profiler organisms.
• g:Sorter searches for similar expression profiles to a given gene, protein or probe in a large set of public microarray datasets from the Gene Expression Omnibus (GEO) database.
• g:Cocoa provides a compact interface for comparing enrichments of multiple gene lists.

• ontology or annotation visualization
• statistical analysis
• slimmer-type tool
• term enrichment
• protein interactions
• functional similarity
• other analysis
• coexpression similarity search, Gene ID conversion, network enrichment analysis., orthology mapping, search by genomic locus

Gene Ontology Browsing Utility (GOBU) (GOBU) is a Java-based software program for integrating biological annotation catalogs under an extendable software architecture. Users may interact with the Gene Ontology and user-defined hierarchy data of genes, and then use its plugins to (and not limited to) (1) browse the GO hierarchy with user defined data, (2) browse GO-oriented expression levels in the user data, (3) compute GO enrichment, and/or (4) customize data reporting.
A set of classes and utility functions has been established so that a customized program can be made as a plugin or a command-line tool that programmically manipulate the Gene Ontology and specified user data. See the source code repository for examples.

• ontology or annotation browser
• ontology or annotation visualization
• software library
• statistical analysis
• term enrichment

Gene Ontology For Functional Analysis (GOFFA) is a tool developed for ArrayTrack that takes a list of genes and identifies terms in Gene Ontology associated with those genes. GOFFA provides tools to view/access the following:
* GO term hierarchy
* Full listing of GO terms annotated with the genes associated with a given term
* Fisher's exact test p-value providing the probability of identifying that many genes for a given term by chance alone
* Relative enrichment factor (E-value) giving the enrichment of a GO term for genes in the submitted list relative to the frequency of genes assigned to that term from the full set of GOFFA annotated genes for a particular species

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• term enrichment
• text mining

The Generic GO Term Finder finds the significant GO terms shared among a list of genes from your organism of choice, displaying the results in a table and as a graph (showing the terms and their ancestry). The user may optionally provide background information or a custom gene association file or filter evidence codes. This tool is capable of batch processing multiple queries at once.

• ontology or annotation visualization
• term enrichment

GeneTools is a collection of web-based tools that brings together information from a broad range of resources, and provides this in a manner particularly useful for genome-wide analyses. Today, the two main tools connected to this database are the NMC Annotation Database V2.0 and eGOn V2.0 (explore Gene Ontology).

The NMC Annotation Database V2.0 provides information from UniGene, EntrezGene, SwissProt and Gene Ontology (GO). Major features are:

• Single search/Batch search, extraction of data for single or batches of genes.
• Manage reporter lists: in folders and share selected lists with other users.
• Manual GO Annotation: add your own Gene Ontology (GO) annotations to genes of interest.
• Export: to Excel, text or XML format.

eGOn V2.0 facilitates interpretation of GO annotation. GO terms are retrieved in batch modus from EntrezGene and the GO database and displayed in the GO directed acyclic hierarchical graph (DAG). Essential features of eGOn V2.0 are:

• Visualization: gene annotations are visualized in the GO DAG or as a table view. The granularity of the GO DAG can be edited freely by the user.
• Filtering: GO annotations can be filtered on evidence codes.
• Include user defined GO annotations: previously added to the Annotation database.
• Statistical analysis: Several gene lists are analyzed simultaneously to compare the distribution of the annotated genes over the GO hierarchy.

Statistical tests are implemented to allow the user to compute GO annotation dissimilarity within or between gene lists.

• Connection to Annotation database: Links to Annotation database gene and protein information are offered directly from the GO DAG or in exported data.
• Export: GO DAG information, statistical results and gene and protein information can be exported in excel, text or XML format.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• statistical analysis
• term enrichment

GOrilla is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets. These are determined in a data driven manner. GOrilla employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the top of a ranked gene list. The tool supports several input formats: gene symbol, gene and protein RefSeq, Uniprot, Unigene and Ensembl. Supported organisms include: human, mouse, rat, yeast, zebrafish, D. melanogaster, C. elegans and A. thaliana. The input to GOrilla is either a ranked gene list or target and background sets. The graphical output shows the results in the context of the GO DAG.

• ontology or annotation visualization
• statistical analysis
• term enrichment

GOTaxExplorer presents a new approach to comparative genomics that integrates functional information and families with the taxonomic classification. It integrates UniProt, Gene Ontology, NCBI Taxonomy, Pfam and SMART in one database. GOTaxExplorer provides four different query types: selection of entity sets, comparison of sets of Pfam families, semantic comparison of sets of GO terms, functional comparison of sets of gene products.
This permits to select custom sets of GO terms, families or taxonomic groups. For example, it is possible to compare arbitrarily selected organisms or groups of organisms from the taxonomic tree on the basis of the functionality of their genes. Furthermore, it enables to determine the distribution of specific molecular functions or protein families in the taxonomy. The comparison of sets of GO terms allows to assess the semantic similarity of two different GO terms. The functional comparison of gene products makes it possible to identify functionally equivalent and functionally related gene products from two organisms on the basis of GO annotations and a semantic similarity measure for GO.

• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• functional similarity
• semantic similarity
• other analysis
• comparative genomics analysis

GraphWeb allows the detection of modules from biological, heterogeneous and multi-species networks, and the interpretation of detected modules using Gene Ontology, cis-regulatory motifs and biological pathways.

• ontology or annotation visualization
• statistical analysis
• term enrichment
• protein interactions
• Gene ID conversion; orthology mapping; network visualisation; graph clustering

With the MGI GO Browser, you can search for a GO term and view all mouse genes annotated to the term or any subterms. You can also browse the ontologies to view relationships between terms, term definitions, as well as the number of mouse genes annotated to a given term and its subterms. The MGI GO browser directly accesses the GO data in the MGI database, which is updated nightly.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization

OBO-Edit is an open source, platform-independent application for viewing and editing any OBO format ontologies. OBO-Edit is a graph-based tool; its emphasis on the overall graph structure of an ontology provides a friendly interface for biologists, and makes OBO-Edit excellent for the rapid generation of large ontologies focusing on relationships between relatively simple classes.

OBO-Edit uses the OBO format flat file.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• ontology or annotation editor

Microarrays are at the center of a revolution in biotechnology, allowing researchers to screen tens of thousands of genes simultaneously. Typically, they have been used in exploratory research to help formulate hypotheses. In most cases, this phase is followed by a more focused, hypothesis driven stage in which certain specific biological processes and pathways are thought to be involved. Since a single biological process can still involve hundreds of genes, microarrays are still the preferred approach as proven by the availability of focused arrays from several manufacturers. Since focused arrays from different manufacturers use different sets of genes, each array will represent any given regulatory pathway to a different extent. We argue that a functional analysis of the arrays available should be the most important criterion used in the array selection. We developed Onto-Compare as a database that can provide this functionality, based on the GO nomenclature.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• other analysis
• compare commercially available microarrays based on GO

Many Laboratories chose to design and print their own microarrays. At present, the choice of the genes to include on a certain microarray is a very laborious process requiring a high level of expertise. Onto-Design database is able to assist the designers of custom microarrays by providing the means to select genes based on their experiment.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• other analysis
• design custom microarrays based on GO terms of interest

The typical result of a microarray experiment is a list of tens or hundreds of genes found to be differentially regulated in the condition under study. Independently of the methods used to select these genes, the common task faced by any researcher is to translate these lists of genes into a better understanding of the biological phenomena involved. Currently, this is done through a tedious combination of searches through the literature and a number of public databases. We developed Onto-Express (OE) as a novel tool able to automatically translate such lists of differentially regulated genes into functional profiles characterizing the impact of the condition studied. OE constructs functional profiles (using Gene Ontology terms) for the following categories: biochemical function, biological process, cellular role, cellular component, molecular function and chromosome location. Statistical significance values are calculated for each category. We demonstrated the validity and the utility of this comprehensive global analysis of gene function by analyzing two breast cancer data sets from two separate laboratories. OE was able to identify correctly all biological processes postulated by the original authors, as well as discover novel relevant mechanisms (Draghici et.al, Genomics, 81(2), 2003). Other results obtained with Onto-Express can be found in Khatri et.al., Genomics. 79(2), 2002.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• statistical analysis
• term enrichment
• other analysis
• custom level of abstraction of the Gene Ontology

Onto-Express is a web-based tool in the Onto-Tools suite that performs automated function profiling for a list of differentially expressed genes. However, Onto-Express does not support functional profiling for the organisms that do not have annotations in public domain, or use of custom (i.e. user-defined) ontologies. This limitation is also true for most of the other existing tools for functional profiling (10), which means that researchers working with uncommon organisms and/or new annotations or ontologies may be forced to construct such profiles manually. Onto-Express To Go (OE2GO) is a new tool added to the Onto-Tools ensemble to address these issues. OE2GO is built on top of OE to leverage its existing functionality. In OE2GO, the users now have an option to use either the Onto-Tools database as a source of functional annotations or provide their own annotations in a separate file. Currently, OE2GO supports annotation file in the Gene Ontology format.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• statistical analysis
• term enrichment
• other analysis
• custom annotations, custom level of abstraction

OntoVisT is a general purpose ontological visualization tool. Ontologies have emerged as a fast growing research topic in the area of semantic web during last decade. Currently there are 204 ontologies that are available through OBO Foundry and BioPortal. Several excellent tools for navigating the ontological structure are available, however most of them are dedicated to a specific annotation data or integrated with specific analysis applications, and do not offer flexibility in terms of general-purpose usage for ontology exploration.
We developed OntoVisT, a web based ontological visualization tool. This application is designed for interactive visualization of any ontological hierarchy for a specific node of interest, up to the chosen level of children and/or ancestor. It takes any ontology file in OBO format as input and generates output as DAG hierarchical graph for the chosen query. To enhance the navigation capabilities of complex networks, we have embedded several features such as search criteria, zoom in/out, center focus, nearest neighbor highlights and mouse hover events. The application has been tested on all 72 data sets available in OBO format through OBO foundry. The results for few of them can be accessed through OntoVisT-Gallery.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• in such a way that it contains both the property of DAG as well as placement of all child nodes below their parent nodes. The advantage of this representation is the flow of information is uni-directional, The tool is designed to improve the interpretability by modifying the structure in DAG hierarchical form, which reduces the effort to interpret the network.

QuickGO is a web-based tool that allows easy browsing of the Gene Ontology (GO) and all associated electronic and manual GO annotations provided by the GO Consortium annotation groups. QuickGO offers a range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation.

• ontology or annotation browser
• ontology or annotation search engine
• ontology or annotation visualization
• database or data warehouse
• slimmer-type tool

RamiGO is a Bioconductor.org software package available for the statistical programming language R and provides an interface for sending requests to the AmiGO visualize web server, retrieving DAG GO trees, parsing GraphViz DOT format files, exporting GML files for Cytoscape and also for interactively displaying GO trees, received from AmiGO visualize, in Cytoscape without importing or exporting them.
RamiGO utilizes the visualization of GO trees from AmiGO and makes it available from R.

• ontology or annotation search engine
• ontology or annotation visualization
• other analysis

REViGO summarizes lists of Gene Ontology terms by removing redundant terms and visualizing the remaining ones in scatterplots, interactive graphs, treemaps, or tag clouds

• ontology or annotation visualization
• statistical analysis

StRAnGER (Statistical Ranking of ANotated Genomic Experimental Results) is a web application for the automated statistical analysis of annotated gene profiling experiments, exploiting controlled biological vocabularies, like the Gene Ontology or the KEGG pathways terms. Starting from annotated lists of differentially expressed genes StRAnGER repartitions and reorders the initial distribution of terms to define a new distribution of elements where each element pools terms holding the same enrichment score. The elements are then prioritized according to StRAnGER's algorithm and, by applying bootstrapping techniques, a corrected measure of the statistical significance of these elements is derived, enabling the selection of terms mapped to these elements, unambiguously associated with respective significant gene sets. Besides their high statistical score, another selection criterion for the terms is the number of their members, something that incurs a biological prioritization in line with a Systems Biology context.

• ontology or annotation visualization
• statistical analysis
• term enrichment

The Software Tool for Rapid Annotation of Proteins saves you time by automatically annotating a protein list with information that helps you meaningfully interpret your mass spectrometry data. STRAP takes protein lists as input, in the form of plain text files, protXML files (usually from the TPP), or Dat files from MASCOT search results. From this, STRAP generates protein annotation tables, and a variety of GO charts to aid individual and differential analysis of proteomics data, as shown below. It downloads information from mainly the Uniprot and EBI QuickGO databases. STRAP requires Windows XP or higher with at least version 3.5 of the Microsoft .NET Framework installed.

• ontology or annotation browser
• ontology or annotation visualization
• Differential analysis of proteomics data sets

Flash GViewer is a customizable Flash movie that can be easily inserted into a web page to display each chromosome in a genome along with the locations of individual features on the chromosomes. It is intended to provide an overview of the genomic locations of a specific set of features - eg. genes associated with a specific ontology term, etc., rather than as a way to view all features on the genome. The features can hyperlink out to a detail page to enable to GViewer to be used as a navigation tool. Genome maps for Rat, Mouse, Human and C. elegans are provided but other genome maps can be easily created. Annotation data can be provided as static text files or produced as XML via server scripts.
This tool is not GO-specific, but was built for the purpose of viewing GO annotation data.

• ontology or annotation visualization

Web Gene Ontology Annotation Plot (WEGO) is a simple but useful tool for plotting Gene Ontology (GO) annotation results. Different from other commercial software for chart creating, WEGO is designed to deal with the directed acyclic graph (DAG) structure of GO to facilitate histogram creation of GO annotation results. WEGO has been widely used in many important biological research projects, such as the rice genome project and the silkworm genome project. It has become one of the useful tools for downstream gene annotation analysis, especially when performing comparative genomics tasks.

• ontology or annotation visualization