Dataset Information

Visual annotation display (VLAD): a tool for finding functional themes in lists of genes.

ABSTRACT: Experiments that employ genome scale technology platforms frequently result in lists of tens to thousands of genes with potential significance to a specific biological process or disease. Searching for biologically relevant connections among the genes or gene products in these lists is a common data analysis task. We have implemented a software application for uncovering functional themes in sets of genes based on their annotations to bio-ontologies, such as the gene ontology and the mammalian phenotype ontology. The application, called VisuaL Annotation Display (VLAD), performs a statistical analysis to test for the enrichment of ontology terms in a set of genes submitted by a researcher. The results for each analysis using VLAD includes a table of ontology terms, sorted in decreasing order of significance. Each row contains the term, statistics such as the number of annotated terms, the p value, etc., and the symbols of annotated genes. An accompanying graphical display shows portions of the ontology hierarchy, where node sizes are scaled based on p values. Although numerous ontology term enrichment programs already exist, VLAD is unique in that it allows users to upload their own annotation files and ontologies for customized term enrichment analyses, supports the analysis of multiple gene sets at once, provides interfaces to customize graphical output, and is tightly integrated with functional and biological details about mouse genes in the Mouse Genome Informatics (MGI) database. VLAD is available as a web-based application from the MGI web site (http://proto.informatics.jax.org/prototypes/vlad/).

SUBMITTER: Richardson JE

PROVIDER: S-EPMC4602057 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Visual annotation display (VLAD): a tool for finding functional themes in lists of genes.

Richardson Joel E JE Bult Carol J CJ

Mammalian genome : official journal of the International Mammalian Genome Society 20150606 9-10

Experiments that employ genome scale technology platforms frequently result in lists of tens to thousands of genes with potential significance to a specific biological process or disease. Searching for biologically relevant connections among the genes or gene products in these lists is a common data analysis task. We have implemented a software application for uncovering functional themes in sets of genes based on their annotations to bio-ontologies, such as the gene ontology and the mammalian p ...[more]

PMID: 26047590

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Project description:BACKGROUND:Analysis of any newly sequenced bacterial genome starts with the identification of protein-coding genes. Despite the accumulation of multiple complete genome sequences, which provide useful comparisons with close relatives among other organisms during the annotation process, accurate gene prediction remains quite difficult. A major reason for this situation is that genes are tightly packed in prokaryotes, resulting in frequent overlap. Thus, detection of translation initiation sites and/or selection of the correct coding regions remain difficult unless appropriate biological knowledge (about the structure of a gene) is imbedded in the approach. RESULTS:We have developed a new program that automatically identifies biologically significant candidate genes in a bacterial genome. Twenty-six complete prokaryotic genomes were analyzed using this tool, and the accuracy of gene finding was assessed by comparison with existing annotations. This analysis revealed that, despite the enormous effort of genome program annotators, a small but not negligible number of genes annotated within the framework of sequencing projects are likely to be partially inaccurate or plainly wrong. Moreover, the analysis of several putative new genes shows that, as expected, many short genes have escaped annotation. In most cases, these new genes revealed frameshifts that could be either artifacts or genuine frameshifts. Some entirely unexpected new genes have also been identified. This allowed us to get a more complete picture of prokaryotic genomes. The results of this procedure are progressively integrated into the SWISS-PROT reference databank. CONCLUSIONS:The results described in the present study show that our procedure is very satisfactory in terms of gene finding accuracy. Except in few cases, discrepancies between our results and annotations provided by individual authors can be accounted for by the nature of each annotation process or by specific characteristics of some genomes. This stresses that close cooperation between scientists, regular update and curation of the findings in databases are clearly required to reduce the level of errors in genome annotation (and hence in reducing the unfortunate spreading of errors through centralized data libraries).

Dataset Information

Visual annotation display (VLAD): a tool for finding functional themes in lists of genes.

Publications

Visual annotation display (VLAD): a tool for finding functional themes in lists of genes.

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