TreeQ-VISTA: an interactive tree visualization tool with functional annotation query capabilities

We describe a general multiplatform exploratory tool called TreeQ-Vista, designed for presenting functional annotations in a phylogenetic context. Traits, such as phenotypic and genomic properties, are interactively queried from a user-provided relational database with a user-friendly interface which provides a set of tools for users with or without SQL knowledge. The query results are projected onto a phylogenetic tree and can be displayed in multiple color groups. A rich set of browsing, grouping and query tools are provided to facilitate trait exploration, comparison and analysis. AVAILABILITY: The program, detailed tutorial and examples are available online (http:/genome.lbl.gov/vista/TreeQVista).     

The SOFG Anatomy Entry List (SAEL): an annotation tool for functional genomics data

A great deal of data in functional genomics studies needs to be annotated with low-resolution anatomical terms. For example, gene expression assays based on manually dissected samples (microarray, SAGE, etc.) need high-level anatomical terms to describe sample origin. First-pass annotation in high-throughput assays (e.g. large-scale in situ gene expression screens or phenotype screens) and bibliographic applications, such as selection of keywords, would also benefit from a minimum set of standard anatomical terms. Although only simple terms are required, the researcher faces serious practical problems of inconsistency and confusion, given the different aims and the range of complexity of existing anatomy ontologies. A Standards and Ontologies for Functional Genomics (SOFG) group therefore initiated discussions between several of the major anatomical ontologies for higher vertebrates. As we report here, one result of these discussions is a simple, accessible, controlled vocabulary of gross anatomical terms, the SOFG Anatomy Entry List (SAEL). The SAEL is available from http://www.sofg.org and is intended as a resource for biologists, curators, bioinformaticians and developers of software supporting functional genomics. It can be used directly for annotation in the contexts described above. Importantly, each term is linked to the corresponding term in each of the major anatomy ontologies. Where the simple list does not provide enough detail or sophistication, therefore, the researcher can use the SAEL to choose the appropriate ontology and move directly to the relevant term as an entry point. The SAEL links will also be used to support computational access to the respective ontologies.     

EasyGO: Gene Ontology-based annotation and functional enrichment analysis tool for agronomical species

Following the publication of our recent article (Kapp et al., BMC Genomics 2006, 7:231), we (the authors) regrettably found several errors in the published Table 5. This correction article not only describes what makes the published Table 5 incorrect, it also presents the correct Table 5.     

Recombineering: a powerful new tool for mouse functional genomics

Highly efficient phage-based Escherichia coli homologous recombination systems have recently been developed that enable genomic DNA in bacterial artificial chromosomes to be modified and subcloned, without the need for restriction enzymes or DNA ligases. This new form of chromosome engineering, termed recombinogenic engineering or recombineering, is efficient and greatly decreases the time it takes to create transgenic mouse models by traditional means. Recombineering also facilitates many kinds of genomic experiment that have otherwise been difficult to carry out, and should enhance functional genomic studies by providing better mouse models and a more refined genetic analysis of the mouse genome.     

GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

Background

Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult.

Results

S TAR N ET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. S TAR N ET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new H EAT S EEKER module.

Conclusion

S TAR N ET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to compare two networks. The list of genes in a S TAR N ET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at http://vanburenlab.medicine.tamhsc.edu/starnet2.html, and does not require user registration.     

Functional annotation by identification of local surface similarities: a novel tool for structural genomics

Background  

Protein function is often dependent on subsets of solvent-exposed residues that may exist in a similar three-dimensional configuration in non homologous proteins thus having different order and/or spacing in the sequence. Hence, functional annotation by means of sequence or fold similarity is not adequate for such cases.     

ProFAT: a web-based tool for the functional annotation of protein sequences

Background  

The functional annotation of proteins relies on published information concerning their close and remote homologues in sequence databases. Evidence for remote sequence similarity can be further strengthened by a similar biological background of the query sequence and identified database sequences. However, few tools exist so far, that provide a means to include functional information in sequence database searches.     

Metalloproteomics: high-throughput structural and functional annotation of proteins in structural genomics

A high-throughput method for measuring transition metal content based on quantitation of X-ray fluorescence signals was used to analyze 654 proteins selected as targets by the New York Structural GenomiX Research Consortium. Over 10% showed the presence of transition metal atoms in stoichiometric amounts; these totals as well as the abundance distribution are similar to those of the Protein Data Bank. Bioinformatics analysis of the identified metalloproteins in most cases supported the metalloprotein annotation; identification of the conserved metal binding motif was also shown to be useful in verifying structural models of the proteins. Metalloproteomics provides a rapid structural and functional annotation for these sequences and is shown to be approximately 95% accurate in predicting the presence or absence of stoichiometric metal content. The project's goal is to assay at least 1 member from each Pfam family; approximately 500 Pfam families have been characterized with respect to transition metal content so far.     

MAAP: a versatile and universal tool for genome analysis

Multiple arbitrary amplicon profiling (MAAP) uses one or more oligonucleotide primers (5 nt) of arbitrary sequence to initiate DNA amplification and generate characteristic fingerprints from anonymous genomes or DNA templates. MAAP markers can be used in general fingerprinting as well as in mapping applications, either directly or as sequence-characterized amplified regions (SCARs). MAAP profiles can be tailored in the number of monomorphic and/or polymorphic products. For example, multiple endonuclease digestion of template DNA or the use of mini-hairpin primers can enhance detection of polymorphic DNA. Comparison of the expected and actual number of amplification products produced with primers differing in length, sequence and GC content from templates of varying complexity reveal severe departures from theoretical formulations with interesting implications in primer-template interaction. Extensive primer-template mismatching can occur when using templates of low complexity or long primers. Primer annealing and extension appears directed by an 8 nt 3-terminal primer domain, requires sites with perfect homology to the first 5–6 nt fom the 3 terminus, and involves direct physical interaction between amplicon annealing sites.     

GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

Background  

Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database. In particular, a variety of tools that perform GO enrichment analysis are currently available. Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set. A few tools also exist that support analyzing ranked lists. The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results.     

BisoGenet: a new tool for gene network building,visualization and analysis

Background  

The increasing availability and diversity of omics data in the post-genomic era offers new perspectives in most areas of biomedical research. Graph-based biological networks models capture the topology of the functional relationships between molecular entities such as gene, protein and small compounds and provide a suitable framework for integrating and analyzing omics-data. The development of software tools capable of integrating data from different sources and to provide flexible methods to reconstruct, represent and analyze topological networks is an active field of research in bioinformatics.