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GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response.

Zaag R, Tamby JP, Guichard C, Tariq Z, Rigaill G, Delannoy E, Renou JP, Balzergue S, Mary-Huard T, Aubourg S, Martin-Magniette ML, Brunaud V - Nucleic Acids Res. (2014)

Bottom Line: To characterize functions associated with these clusters, various resources are analyzed and integrated: Gene Ontology, subcellular localization of proteins, Hormone Families, Transcription Factor Families and a refined stress-related gene list associated to publications.GEM2Net presents the analysis of the 18 stress categories, in which 17,264 genes are involved and organized within 681 co-expression clusters.The meta-data analyses were stored and organized to compose a dynamic Web resource.

View Article: PubMed Central - PubMed

Affiliation: INRA, Unité de Recherche en Génomique Végétale, UMR 1165, ERL CNRS 8196, Saclay Plant Sciences, CP 5708, F-91057 Evry, France UEVE, Unité de Recherche en Génomique Végétale, UMR 1165, ERL CNRS 8196, Saclay Plant Sciences, CP 5708, F-91057 Evry, France.

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Meta-analyses overview for Cluster_49 of the ‘Virus’ stress category. Synoptic view of the meta-data analyses performed on the cluster_49 is shown in the central panel and results of all analyses are summarized in the frame table on the upper right side. Part list of the genes involved in the Biological Process bias is seen below the central panel. In this table, each gene accession is tagged with colored circle(s) (legend table on the left) and other meta-data enrichments are indicated on the right with blue points when appropriate.
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Figure 4: Meta-analyses overview for Cluster_49 of the ‘Virus’ stress category. Synoptic view of the meta-data analyses performed on the cluster_49 is shown in the central panel and results of all analyses are summarized in the frame table on the upper right side. Part list of the genes involved in the Biological Process bias is seen below the central panel. In this table, each gene accession is tagged with colored circle(s) (legend table on the left) and other meta-data enrichments are indicated on the right with blue points when appropriate.

Mentions: The GEM2Net Web interface (http://urgv.evry.inra.fr/GEM2NET) allows users to query the database by stress category or to submit a list of genes of interest to retrieve the stress categories they are implicated in. It is possible to answer questions like ‘are my genes of interest involved in the same co-expression unit?’ by exploring graphically the results of meta-data analyses. To identify at a glance and summarize the potential functional biases of each cluster, GEM2Net proposes an original representation and interactive visualization, using pie charts and graphs. For each stress category, cluster annotation analyses are divided into several tabs, one per meta-data type, which allow the organization of complex and abundant results. In such tabs, a central panel displays every cluster as a pie chart whose diameter is directly related to the total number of genes in the cluster. Colored sections within a pie chart materialize the numbers of genes of the corresponding meta-data when over-represented. For example, Figure 3 presents a view of clusters enrichment analyses for the GO Slim branch ‘Biological Process’ of the ‘Virus’ stress category. Complementary information related to each cluster is also available in a table nearby the central panel, which appears when moving the mouse over a given cluster. In Figure 4, a synthetic view of one cluster, the cluster_49 from the ‘Virus’ stress category, shows a summary of all the meta-data analyses done for this cluster. In each pie chart, significant enrichments are seen in color for few meta-data analyses, e.g. in the GO terms ‘cell organization and biogenesis’ and ‘response to stress’ of the ‘Biological Process’ ontology. The complete list of 213 genes of cluster_49 appears in a table sorted by gene roles in the selected meta-data type and highlights their implication in other biases by colored circles.


GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response.

Zaag R, Tamby JP, Guichard C, Tariq Z, Rigaill G, Delannoy E, Renou JP, Balzergue S, Mary-Huard T, Aubourg S, Martin-Magniette ML, Brunaud V - Nucleic Acids Res. (2014)

Meta-analyses overview for Cluster_49 of the ‘Virus’ stress category. Synoptic view of the meta-data analyses performed on the cluster_49 is shown in the central panel and results of all analyses are summarized in the frame table on the upper right side. Part list of the genes involved in the Biological Process bias is seen below the central panel. In this table, each gene accession is tagged with colored circle(s) (legend table on the left) and other meta-data enrichments are indicated on the right with blue points when appropriate.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4383956&req=5

Figure 4: Meta-analyses overview for Cluster_49 of the ‘Virus’ stress category. Synoptic view of the meta-data analyses performed on the cluster_49 is shown in the central panel and results of all analyses are summarized in the frame table on the upper right side. Part list of the genes involved in the Biological Process bias is seen below the central panel. In this table, each gene accession is tagged with colored circle(s) (legend table on the left) and other meta-data enrichments are indicated on the right with blue points when appropriate.
Mentions: The GEM2Net Web interface (http://urgv.evry.inra.fr/GEM2NET) allows users to query the database by stress category or to submit a list of genes of interest to retrieve the stress categories they are implicated in. It is possible to answer questions like ‘are my genes of interest involved in the same co-expression unit?’ by exploring graphically the results of meta-data analyses. To identify at a glance and summarize the potential functional biases of each cluster, GEM2Net proposes an original representation and interactive visualization, using pie charts and graphs. For each stress category, cluster annotation analyses are divided into several tabs, one per meta-data type, which allow the organization of complex and abundant results. In such tabs, a central panel displays every cluster as a pie chart whose diameter is directly related to the total number of genes in the cluster. Colored sections within a pie chart materialize the numbers of genes of the corresponding meta-data when over-represented. For example, Figure 3 presents a view of clusters enrichment analyses for the GO Slim branch ‘Biological Process’ of the ‘Virus’ stress category. Complementary information related to each cluster is also available in a table nearby the central panel, which appears when moving the mouse over a given cluster. In Figure 4, a synthetic view of one cluster, the cluster_49 from the ‘Virus’ stress category, shows a summary of all the meta-data analyses done for this cluster. In each pie chart, significant enrichments are seen in color for few meta-data analyses, e.g. in the GO terms ‘cell organization and biogenesis’ and ‘response to stress’ of the ‘Biological Process’ ontology. The complete list of 213 genes of cluster_49 appears in a table sorted by gene roles in the selected meta-data type and highlights their implication in other biases by colored circles.

Bottom Line: To characterize functions associated with these clusters, various resources are analyzed and integrated: Gene Ontology, subcellular localization of proteins, Hormone Families, Transcription Factor Families and a refined stress-related gene list associated to publications.GEM2Net presents the analysis of the 18 stress categories, in which 17,264 genes are involved and organized within 681 co-expression clusters.The meta-data analyses were stored and organized to compose a dynamic Web resource.

View Article: PubMed Central - PubMed

Affiliation: INRA, Unité de Recherche en Génomique Végétale, UMR 1165, ERL CNRS 8196, Saclay Plant Sciences, CP 5708, F-91057 Evry, France UEVE, Unité de Recherche en Génomique Végétale, UMR 1165, ERL CNRS 8196, Saclay Plant Sciences, CP 5708, F-91057 Evry, France.

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Related in: MedlinePlus