Immune and Inflammatory Disease Portal - Tools
Data Mining and Analysis:
- Gene Annotator RGD's Gene Annotator takes a list of gene symbols, RGD IDs, GenBank accession numbers, Ensembl identifiers, and/or a chromosomal region, and retrieves annotation data from RGD. The tool will retrieve annotations from any or all ontologies used at RGD for genes and their orthologs, as well as links to additional information at other databases. To explore a specific list of genes from this portal, simply select your term(s) of interest, copy the gene symbols from the "Genes Info" box on the portal page and paste them into the entry box in the GA Tool.
- RatMine RatMine integrates data from RGD, UniProtKB, Ensembl, NCBI, PubMed and KEGG to form a web-based data warehousing, mining and analysis tool tailored to the needs of rat researchers. Datasets derived from querying this data or from uploading your own data can be saved, manipulated and/or downloaded for use in other applications. For your convenience, a list of genes for each RGD Disease Portal is available in RatMine. Click here to view all of RatMine's public lists.
- PhenoMiner RGD's PhenoMiner is a powerful and flexible tool with which to select rat strains, experimental conditions, measurement methods and phenotypes in order to focus in on the results which are of the most interest and utility to them, and to compare results across multiple experiments. Unlike other methods which only compare terms, PhenoMiner allows researchers to view and download specific numerical data for phenotypes.
- Rat Genome Browser In addition to the typical gene tracks, RGD's Genome Browser provides QTL and SNP tracks, RGD Congenic Strain tracks, Strain-specific variant tracks and more to facilitate the search for candidate variations that might be linked to a disease or phenotype. Gene and QTL tracks link to RGD's records, giving convenient access to a wide range of biological information. In addition to the Rat GBrowse, RGD also offers a Human Genome Browser. Both browsers include synteny tracks and inter-browser links which allow researchers to compare syntenic regions between the two species. Both browsers also now feature specific tracks for disease-related data, such as the Immune System Diseases tracks, which utilize RGD's extensive Disease Ontology annotations to present genes, QTLs and strains with demonstrated associations to a particular disease category.
- GViewer Gviewer provides users with a complete genome view of genes and QTLs annotated to a function, biological process, cellular component, phenotype, disease, or pathway.
- VCMap The Virtual Comparative Map allows users to compare genomic regions, genes and QTLs across six different species: rat, mouse, human, cow, pig and chicken.
- UCSC Browser
- Ensembl Browser
- NCBI MapViewer
Ontology Analysis Tools:
- GOMiner GoMiner leverages the Gene Ontology to identify the biological processes, functions and components represented in these lists. Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. The insights gained through GoMiner can generate hypotheses to guide additional research.
- Onto-Express , Onto-Compare , Onto-Design , Onto-Translate 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. Additional tools are provided for microarray data storing and analysis.
- DAVID Bioinformatics
Resources The Database for Annotation, Visualization and Integrated Discovery (DAVID) provides a "comprehensive set of functional annotation tools for investigators to understand biological meaning behind a large list of genes". By uploading up to 3000 gene identifiers (e.g. IDs from RGD, Entrez Gene, Ensembl, Affymetrix, Agilent, etc) users can leverage the "numerous public sources of protein and gene annotations [which] have been parsed and integrated into DAVID" to analyze the functional annotations, pathway and disease associations, gene similarity and functional categories of their genes of interest.