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GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies.

Zhang B, Schmoyer D, Kirov S, Snoddy J - BMC Bioinformatics (2004)

Bottom Line: GOTree Machine generates a GOTree, a tree-like structure to navigate the Gene Ontology Directed Acyclic Graph for input gene sets.This system provides user friendly data navigation and visualization.Statistical analysis helps users to identify the most important Gene Ontology categories for the input gene sets and suggests biological areas that warrant further study.

View Article: PubMed Central - HTML - PubMed

Affiliation: Graduate School in Genome Science and Technology, University of Tennessee-Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. zhangb@ornl.gov

ABSTRACT

Background: Microarray and other high-throughput technologies are producing large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in the gene sets.

Results: We have created a web-based tool for data analysis and data visualization for sets of genes called GOTree Machine (GOTM). This tool was originally intended to analyze sets of co-regulated genes identified from microarray analysis but is adaptable for use with other gene sets from other high-throughput analyses. GOTree Machine generates a GOTree, a tree-like structure to navigate the Gene Ontology Directed Acyclic Graph for input gene sets. This system provides user friendly data navigation and visualization. Statistical analysis helps users to identify the most important Gene Ontology categories for the input gene sets and suggests biological areas that warrant further study. GOTree Machine is available online at http://genereg.ornl.gov/gotm/.

Conclusion: GOTree Machine has a broad application in functional genomic, proteomic and other high-throughput methods that generate large sets of interesting genes; its primary purpose is to help users sort for interesting patterns in gene sets.

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Related in: MedlinePlus

Output user interface of the GOTM The GOTree window displays the expandable tree structure of the GO categories. Each GO category is followed by three parameters: O (Observed gene number in the category); E (Expected gene number in the category) and R (Ratio of enrichment for the category). The fourth parameter P (p value calculated from the hypergeometric test) is given for the categories with R > 1 to indicate the significance of enrichment. Categories with P < 0.01 are colored red. The gene/category list window displays genes in selected GO categories ("eye morphogenesis" in this case) and the names of enriched GO categories followed by the parameters O, E, R and P. The genes are represented by LocusIDs followed by gene symbols and ratios in the microarray experiment. The gene information window displays the gene information record for the selected gene.
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Figure 3: Output user interface of the GOTM The GOTree window displays the expandable tree structure of the GO categories. Each GO category is followed by three parameters: O (Observed gene number in the category); E (Expected gene number in the category) and R (Ratio of enrichment for the category). The fourth parameter P (p value calculated from the hypergeometric test) is given for the categories with R > 1 to indicate the significance of enrichment. Categories with P < 0.01 are colored red. The gene/category list window displays genes in selected GO categories ("eye morphogenesis" in this case) and the names of enriched GO categories followed by the parameters O, E, R and P. The genes are represented by LocusIDs followed by gene symbols and ratios in the microarray experiment. The gene information window displays the gene information record for the selected gene.

Mentions: Figure 3 shows the output user interface of GOTM. The output view is divided into 3 windows. The upper-left window is the GOTree window, the upper-right window is the gene/category list window and the bottom window is the gene information window. The expandable GOTree will be shown in the GOTree window. The user can browse the tree by clicking the "+" symbol. For single gene set analysis, the number of genes in each GO category will be given. If the interesting gene set vs. reference gene set analysis is selected, three parameters will be given for each GO category: O (observed gene number in the category), E (expected gene number in the category), R (ratio of enrichment for the category). For those GO categories with R > 1, the fourth parameter P indicating significance of enrichment will be given. GO categories with significantly enriched gene numbers (P < 0.01) will be colored red. By clicking on individual GO categories, the genes in the category will be shown in the gene/category list window. It might be sometimes difficult for a user to browse and find the GO category in which the user is interested. In this case, the user can do an exact search for a GO category using "GO Term Search" or a fuzzy key word search using "Keyword Search" at the top of the GOTree window. The returned GO categories and genes inside each category will be shown in the gene/category list window. The number of GO categories with enriched gene numbers will also be shown in the GOTree window. By clicking on the number, the names of enriched GO categories will be shown in the gene/category list window. GOTree provides comprehensive classification of the genes in a hierarchical structure, however, due to the complex structure, it's not easily publishable. After browsing the GOTree, the user may pick appropriate annotation levels and get corresponding bar charts for publication using the Bar Chart button (for an example, see ). GOTree can also be exported and locally stored in html format using the Export GOTree button. Enriched GO categories are colored red, and genes in each category are also included in the exported GOTree (for an example, see ).


GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies.

Zhang B, Schmoyer D, Kirov S, Snoddy J - BMC Bioinformatics (2004)

Output user interface of the GOTM The GOTree window displays the expandable tree structure of the GO categories. Each GO category is followed by three parameters: O (Observed gene number in the category); E (Expected gene number in the category) and R (Ratio of enrichment for the category). The fourth parameter P (p value calculated from the hypergeometric test) is given for the categories with R > 1 to indicate the significance of enrichment. Categories with P < 0.01 are colored red. The gene/category list window displays genes in selected GO categories ("eye morphogenesis" in this case) and the names of enriched GO categories followed by the parameters O, E, R and P. The genes are represented by LocusIDs followed by gene symbols and ratios in the microarray experiment. The gene information window displays the gene information record for the selected gene.
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Related In: Results  -  Collection

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Figure 3: Output user interface of the GOTM The GOTree window displays the expandable tree structure of the GO categories. Each GO category is followed by three parameters: O (Observed gene number in the category); E (Expected gene number in the category) and R (Ratio of enrichment for the category). The fourth parameter P (p value calculated from the hypergeometric test) is given for the categories with R > 1 to indicate the significance of enrichment. Categories with P < 0.01 are colored red. The gene/category list window displays genes in selected GO categories ("eye morphogenesis" in this case) and the names of enriched GO categories followed by the parameters O, E, R and P. The genes are represented by LocusIDs followed by gene symbols and ratios in the microarray experiment. The gene information window displays the gene information record for the selected gene.
Mentions: Figure 3 shows the output user interface of GOTM. The output view is divided into 3 windows. The upper-left window is the GOTree window, the upper-right window is the gene/category list window and the bottom window is the gene information window. The expandable GOTree will be shown in the GOTree window. The user can browse the tree by clicking the "+" symbol. For single gene set analysis, the number of genes in each GO category will be given. If the interesting gene set vs. reference gene set analysis is selected, three parameters will be given for each GO category: O (observed gene number in the category), E (expected gene number in the category), R (ratio of enrichment for the category). For those GO categories with R > 1, the fourth parameter P indicating significance of enrichment will be given. GO categories with significantly enriched gene numbers (P < 0.01) will be colored red. By clicking on individual GO categories, the genes in the category will be shown in the gene/category list window. It might be sometimes difficult for a user to browse and find the GO category in which the user is interested. In this case, the user can do an exact search for a GO category using "GO Term Search" or a fuzzy key word search using "Keyword Search" at the top of the GOTree window. The returned GO categories and genes inside each category will be shown in the gene/category list window. The number of GO categories with enriched gene numbers will also be shown in the GOTree window. By clicking on the number, the names of enriched GO categories will be shown in the gene/category list window. GOTree provides comprehensive classification of the genes in a hierarchical structure, however, due to the complex structure, it's not easily publishable. After browsing the GOTree, the user may pick appropriate annotation levels and get corresponding bar charts for publication using the Bar Chart button (for an example, see ). GOTree can also be exported and locally stored in html format using the Export GOTree button. Enriched GO categories are colored red, and genes in each category are also included in the exported GOTree (for an example, see ).

Bottom Line: GOTree Machine generates a GOTree, a tree-like structure to navigate the Gene Ontology Directed Acyclic Graph for input gene sets.This system provides user friendly data navigation and visualization.Statistical analysis helps users to identify the most important Gene Ontology categories for the input gene sets and suggests biological areas that warrant further study.

View Article: PubMed Central - HTML - PubMed

Affiliation: Graduate School in Genome Science and Technology, University of Tennessee-Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. zhangb@ornl.gov

ABSTRACT

Background: Microarray and other high-throughput technologies are producing large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in the gene sets.

Results: We have created a web-based tool for data analysis and data visualization for sets of genes called GOTree Machine (GOTM). This tool was originally intended to analyze sets of co-regulated genes identified from microarray analysis but is adaptable for use with other gene sets from other high-throughput analyses. GOTree Machine generates a GOTree, a tree-like structure to navigate the Gene Ontology Directed Acyclic Graph for input gene sets. This system provides user friendly data navigation and visualization. Statistical analysis helps users to identify the most important Gene Ontology categories for the input gene sets and suggests biological areas that warrant further study. GOTree Machine is available online at http://genereg.ornl.gov/gotm/.

Conclusion: GOTree Machine has a broad application in functional genomic, proteomic and other high-throughput methods that generate large sets of interesting genes; its primary purpose is to help users sort for interesting patterns in gene sets.

Show MeSH
Related in: MedlinePlus