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The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease.

Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H - Nucleic Acids Res. (2014)

Bottom Line: Complementing the genomic data catalogs are those associated with phenotypes and disease, including strains, QTL and experimental phenotype measurements across hundreds of strains.Data are submitted by researchers, acquired through bulk data pipelines or curated from published literature.Innovative software tools provide users with an integrated platform to query, mine, display and analyze valuable genomic and phenomic datasets for discovery and enhancement of their own research.

View Article: PubMed Central - PubMed

Affiliation: Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA Department of Surgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA shimoyama@mcw.edu.

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The Gene Annotator Tool. Shown in the center of the figure is the menu bar from the Gene Annotator (GA) tool. The default result is the ‘Annotations’ page (top left), which gives detailed lists of annotations for each gene in the input list and its corresponding orthologs, as well as a list of external database identifiers for that gene with links to additional information at the other databases. The ‘Annotation Distribution’ analysis (bottom left) indicates the percentage of genes in the input list associated with lists of disease, pathway, phenotype, biological process, molecular function, cellular component and chemical interaction terms, beginning with the terms that appear most commonly. Selecting a term shows the subset of the input list of genes that are associated with that term or any more specific term beneath it in the ontology. Check boxes allow the user to select multiple terms within one or across multiple ontologies to see the genes with annotations to all the selected terms. This smaller subset of the original list can then be entered into the GA Tool for further analysis. The ‘Comparison Heat Map’ function (top right) allows users to select any two ontologies, or to view the overlap between two branches of the same ontology. In this case, the number of genes from the original input list which are associated with disease categories under ‘Cerebrovascular Disorders’ and pathway categories under ‘signaling pathways’ are shown, with intersections containing a higher number of associated genes displayed as increasingly darker colors. Finally, the ‘Genome Plot’ (bottom right) shows the location of each gene in the list against the full set of chromosomes for the species, in this case, the rat karyotype, with the chromosomal positions for all the genes in the list presented in a table below the image (not shown). Functionality for the Genome Plot is the same as that described earlier for the Genome Viewer tool.
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Figure 6: The Gene Annotator Tool. Shown in the center of the figure is the menu bar from the Gene Annotator (GA) tool. The default result is the ‘Annotations’ page (top left), which gives detailed lists of annotations for each gene in the input list and its corresponding orthologs, as well as a list of external database identifiers for that gene with links to additional information at the other databases. The ‘Annotation Distribution’ analysis (bottom left) indicates the percentage of genes in the input list associated with lists of disease, pathway, phenotype, biological process, molecular function, cellular component and chemical interaction terms, beginning with the terms that appear most commonly. Selecting a term shows the subset of the input list of genes that are associated with that term or any more specific term beneath it in the ontology. Check boxes allow the user to select multiple terms within one or across multiple ontologies to see the genes with annotations to all the selected terms. This smaller subset of the original list can then be entered into the GA Tool for further analysis. The ‘Comparison Heat Map’ function (top right) allows users to select any two ontologies, or to view the overlap between two branches of the same ontology. In this case, the number of genes from the original input list which are associated with disease categories under ‘Cerebrovascular Disorders’ and pathway categories under ‘signaling pathways’ are shown, with intersections containing a higher number of associated genes displayed as increasingly darker colors. Finally, the ‘Genome Plot’ (bottom right) shows the location of each gene in the list against the full set of chromosomes for the species, in this case, the rat karyotype, with the chromosomal positions for all the genes in the list presented in a table below the image (not shown). Functionality for the Genome Plot is the same as that described earlier for the Genome Viewer tool.

Mentions: The Gene Annotator or GA Tool is a one-stop functional analysis tool for rat, human and mouse genes. For any of the three organisms, users can upload a list of common identifiers from RGD, EntrezGene, GenBank, Ensembl and Affymetrix or search by a chromosomal region or functional ontology identifiers to retrieve comprehensive reports for each gene. The output (Figure 6, top left) contains data related to disease and phenotype, pathway, Gene Ontology, and drug or chemical interactions, as well as dozens of identifiers and links to other sources. Functional analysis of the entire gene list or subsets can be accomplished through the Annotation Distribution Tool and the Comparison Heat Map. The Annotation Distribution Tool (Figure 6, bottom left) provides a dynamic assessment of the functional make-up of the gene list, showing the percentage of genes associated with various diseases, pathways, biological processes and functions. Users can retrieve the genes associated with a particular disease, pathway or function and further analyze this subset for functional commonalities. The tool also facilitates the retrieval of genes associated with multiple functional categories, such as those associated with a particular disease, a set of pathways and a class of drugs. The Comparison Heat Map (Figure 6, top right) visualizes the distribution of genes across two functional parameters such as disease and pathway. Users can choose the ontologies displayed on the X and Y axes and see the number of genes from their original list in the intersection of classes from each of the categories. Leveraging the power of the ontologies, users can expand each category with a click to return more specific categories and the genes with annotations in the cross-section of these. The Genome Plot (Figure 6, bottom right) provides a genome-wide view of positions for genes in the set, as well as the ability to overlay other data such as QTL, in order to see the overlap. For reference, chromosomal positions are listed in a table below the image. The plot also provides direct links to GBrowse where users can add other tracks such as SNPs, QTL, disease or transcripts. Links from the Variant Visualizer and GBrowse to the reports in the GA Tool provide direct access to comprehensive multiorganism functional profiles.


The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease.

Shimoyama M, De Pons J, Hayman GT, Laulederkind SJ, Liu W, Nigam R, Petri V, Smith JR, Tutaj M, Wang SJ, Worthey E, Dwinell M, Jacob H - Nucleic Acids Res. (2014)

The Gene Annotator Tool. Shown in the center of the figure is the menu bar from the Gene Annotator (GA) tool. The default result is the ‘Annotations’ page (top left), which gives detailed lists of annotations for each gene in the input list and its corresponding orthologs, as well as a list of external database identifiers for that gene with links to additional information at the other databases. The ‘Annotation Distribution’ analysis (bottom left) indicates the percentage of genes in the input list associated with lists of disease, pathway, phenotype, biological process, molecular function, cellular component and chemical interaction terms, beginning with the terms that appear most commonly. Selecting a term shows the subset of the input list of genes that are associated with that term or any more specific term beneath it in the ontology. Check boxes allow the user to select multiple terms within one or across multiple ontologies to see the genes with annotations to all the selected terms. This smaller subset of the original list can then be entered into the GA Tool for further analysis. The ‘Comparison Heat Map’ function (top right) allows users to select any two ontologies, or to view the overlap between two branches of the same ontology. In this case, the number of genes from the original input list which are associated with disease categories under ‘Cerebrovascular Disorders’ and pathway categories under ‘signaling pathways’ are shown, with intersections containing a higher number of associated genes displayed as increasingly darker colors. Finally, the ‘Genome Plot’ (bottom right) shows the location of each gene in the list against the full set of chromosomes for the species, in this case, the rat karyotype, with the chromosomal positions for all the genes in the list presented in a table below the image (not shown). Functionality for the Genome Plot is the same as that described earlier for the Genome Viewer tool.
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Related In: Results  -  Collection

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Figure 6: The Gene Annotator Tool. Shown in the center of the figure is the menu bar from the Gene Annotator (GA) tool. The default result is the ‘Annotations’ page (top left), which gives detailed lists of annotations for each gene in the input list and its corresponding orthologs, as well as a list of external database identifiers for that gene with links to additional information at the other databases. The ‘Annotation Distribution’ analysis (bottom left) indicates the percentage of genes in the input list associated with lists of disease, pathway, phenotype, biological process, molecular function, cellular component and chemical interaction terms, beginning with the terms that appear most commonly. Selecting a term shows the subset of the input list of genes that are associated with that term or any more specific term beneath it in the ontology. Check boxes allow the user to select multiple terms within one or across multiple ontologies to see the genes with annotations to all the selected terms. This smaller subset of the original list can then be entered into the GA Tool for further analysis. The ‘Comparison Heat Map’ function (top right) allows users to select any two ontologies, or to view the overlap between two branches of the same ontology. In this case, the number of genes from the original input list which are associated with disease categories under ‘Cerebrovascular Disorders’ and pathway categories under ‘signaling pathways’ are shown, with intersections containing a higher number of associated genes displayed as increasingly darker colors. Finally, the ‘Genome Plot’ (bottom right) shows the location of each gene in the list against the full set of chromosomes for the species, in this case, the rat karyotype, with the chromosomal positions for all the genes in the list presented in a table below the image (not shown). Functionality for the Genome Plot is the same as that described earlier for the Genome Viewer tool.
Mentions: The Gene Annotator or GA Tool is a one-stop functional analysis tool for rat, human and mouse genes. For any of the three organisms, users can upload a list of common identifiers from RGD, EntrezGene, GenBank, Ensembl and Affymetrix or search by a chromosomal region or functional ontology identifiers to retrieve comprehensive reports for each gene. The output (Figure 6, top left) contains data related to disease and phenotype, pathway, Gene Ontology, and drug or chemical interactions, as well as dozens of identifiers and links to other sources. Functional analysis of the entire gene list or subsets can be accomplished through the Annotation Distribution Tool and the Comparison Heat Map. The Annotation Distribution Tool (Figure 6, bottom left) provides a dynamic assessment of the functional make-up of the gene list, showing the percentage of genes associated with various diseases, pathways, biological processes and functions. Users can retrieve the genes associated with a particular disease, pathway or function and further analyze this subset for functional commonalities. The tool also facilitates the retrieval of genes associated with multiple functional categories, such as those associated with a particular disease, a set of pathways and a class of drugs. The Comparison Heat Map (Figure 6, top right) visualizes the distribution of genes across two functional parameters such as disease and pathway. Users can choose the ontologies displayed on the X and Y axes and see the number of genes from their original list in the intersection of classes from each of the categories. Leveraging the power of the ontologies, users can expand each category with a click to return more specific categories and the genes with annotations in the cross-section of these. The Genome Plot (Figure 6, bottom right) provides a genome-wide view of positions for genes in the set, as well as the ability to overlay other data such as QTL, in order to see the overlap. For reference, chromosomal positions are listed in a table below the image. The plot also provides direct links to GBrowse where users can add other tracks such as SNPs, QTL, disease or transcripts. Links from the Variant Visualizer and GBrowse to the reports in the GA Tool provide direct access to comprehensive multiorganism functional profiles.

Bottom Line: Complementing the genomic data catalogs are those associated with phenotypes and disease, including strains, QTL and experimental phenotype measurements across hundreds of strains.Data are submitted by researchers, acquired through bulk data pipelines or curated from published literature.Innovative software tools provide users with an integrated platform to query, mine, display and analyze valuable genomic and phenomic datasets for discovery and enhancement of their own research.

View Article: PubMed Central - PubMed

Affiliation: Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA Department of Surgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA shimoyama@mcw.edu.

Show MeSH
Related in: MedlinePlus