GeneTools--application for functional annotation and statistical hypothesis testing

Abstract

Background: Modern biology has shifted from "one gene" approaches to methods for genomic-scale analysis like microarray technology, which allow simultaneous measurement of thousands of genes. This has created a need for tools facilitating interpretation of biological data in "batch" mode. However, such tools often leave the investigator with large volumes of apparently unorganized information. To meet this interpretation challenge, gene-set, or cluster testing has become a popular analytical tool. Many gene-set testing methods and software packages are now available, most of which use a variety of statistical tests to assess the genes in a set for biological information. However, the field is still evolving, and there is a great need for "integrated" solutions.

Results: GeneTools is a web-service providing access to a database that brings together information from a broad range of resources. The annotation data are updated weekly, guaranteeing that users get data most recently available. Data submitted by the user are stored in the database, where it can easily be updated, shared between users and exported in various formats. GeneTools provides three different tools: i) NMC Annotation Tool, which offers annotations from several databases like UniGene, Entrez Gene, SwissProt and GeneOntology, in both single- and batch search mode. ii) GO Annotator Tool, where users can add new gene ontology (GO) annotations to genes of interest. These user defined GO annotations can be used in further analysis or exported for public distribution. iii) eGOn, a tool for visualization and statistical hypothesis testing of GO category representation. As the first GO tool, eGOn supports hypothesis testing for three different situations (master-target situation, mutually exclusive target-target situation and intersecting target-target situation). An important additional function is an evidence-code filter that allows users, to select the GO annotations for the analysis.

Conclusion: GeneTools is the first "all in one" annotation tool, providing users with a rapid extraction of highly relevant gene annotation data for e.g. thousands of genes or clones at once. It allows a user to define and archive new GO annotations and it supports hypothesis testing related to GO category representations. GeneTools is freely available through www.genetools.no

Figure 1

Flowchart of the GeneTools program and the underlying database. The underlying database is updated on a weekly basis with annotation information from several external databases including UniGene, Swiss-Prot, Entrez Gene and GO. User data are submitted to the database as text files of gene reporters and analysis of the annotation data can be performed through three user interfaces: the NMC Annotation Tool, the GO Annotator Tool and eGOn. Analysis results and annotation data can be exported in various formats.

Figure 2

Typical "overview" result output for a submitted gene reporter list. Input gene reporter and associated UniGene cluster, gene name, symbol and chromosome localization is shown for all the gene reporters in the submitted lists. Several of the information boxes are hyperlinked redirecting the user to the original source. More specific annotations can be found under the "tabs" named Entrez, SwissProt and GO. By clicking on the gene reporter ID, a single search window for the selected gene reporter will appear.

Figure 3

User interface for the GO Annotator Tool. To add a new GO annotation, the user selects a gene, adds a GO term, chooses an appropriate evidence code and adds a reference article (PMID). The GO annotations are then stored in the database and an exported function to GOA for world wide distribution is under development. A link to the GO Annotator Tool can be launched from the top of the page of the result window from a single gene search, in the NMC Annotation Tool mode.

Figure 4

Result report output from eGOn. Gene reporter lists submitted to eGOn can be visualized in tree-view, as result-view or as report-view. In the tree-view (A) the nodes may be collapsed or expanded producing the desired level of detail and the resulting structure can be saved as a template for future use. Several preset levels can also be selected. By clicking on a GO node the gene reporter associated with this GO node in the GO-tree can be interactively examined and links are offered to single gene view in the NMC Annotation Tool. In result view p-values for all GO categories are shown and for the report view (B), only the GO categories that fit the user's p-value cut-off are shown.

Figure 5

Three different situations covered by the statistical testes in e GOn. Master-target situation: When one gene reporter list is a subset of the other list (the master list) the master-target test can be used in the comparison. Mutually exclusive target-target situation: If the gene reporters do not have any reporters in common (e.g. lists of up- vs. down regulated genes form the same experiment) the mutually exclusive target-target test can be used. Intersecting target-target situation: if the two lists compared include common gene reporters, from e.g. two experiments, then the intersecting target-target test can be used.