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eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes
BACKGROUND: Genetic investigations, boosted by modern sequencing techniques, allow dissecting the genetic component of different phenotypic traits. These efforts result in the compilation of lists of genes related to diseases and show that an increasing number of diseases is associated with multiple...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5558190/ https://www.ncbi.nlm.nih.gov/pubmed/28812536 http://dx.doi.org/10.1186/s12864-017-3911-3 |
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author | Babbi, Giulia Martelli, Pier Luigi Profiti, Giuseppe Bovo, Samuele Savojardo, Castrense Casadio, Rita |
author_facet | Babbi, Giulia Martelli, Pier Luigi Profiti, Giuseppe Bovo, Samuele Savojardo, Castrense Casadio, Rita |
author_sort | Babbi, Giulia |
collection | PubMed |
description | BACKGROUND: Genetic investigations, boosted by modern sequencing techniques, allow dissecting the genetic component of different phenotypic traits. These efforts result in the compilation of lists of genes related to diseases and show that an increasing number of diseases is associated with multiple genes. Investigating functional relations among genes associated with the same disease contributes to highlighting molecular mechanisms of the pathogenesis. RESULTS: We present eDGAR, a database collecting and organizing the data on gene/disease associations as derived from OMIM, Humsavar and ClinVar. For each disease-associated gene, eDGAR collects information on its annotation. Specifically, for lists of genes, eDGAR provides information on: i) interactions retrieved from PDB, BIOGRID and STRING; ii) co-occurrence in stable and functional structural complexes; iii) shared Gene Ontology annotations; iv) shared KEGG and REACTOME pathways; v) enriched functional annotations computed with NET-GE; vi) regulatory interactions derived from TRRUST; vii) localization on chromosomes and/or co-localisation in neighboring loci. The present release of eDGAR includes 2672 diseases, related to 3658 different genes, for a total number of 5729 gene-disease associations. 71% of the genes are linked to 621 multigenic diseases and eDGAR highlights their common GO terms, KEGG/REACTOME pathways, physical and regulatory interactions. eDGAR includes a network based enrichment method for detecting statistically significant functional terms associated to groups of genes. CONCLUSIONS: eDGAR offers a resource to analyze disease-gene associations. In multigenic diseases genes can share physical interactions and/or co-occurrence in the same functional processes. eDGAR is freely available at: edgar.biocomp.unibo.it ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3911-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5558190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-55581902017-08-16 eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes Babbi, Giulia Martelli, Pier Luigi Profiti, Giuseppe Bovo, Samuele Savojardo, Castrense Casadio, Rita BMC Genomics Research BACKGROUND: Genetic investigations, boosted by modern sequencing techniques, allow dissecting the genetic component of different phenotypic traits. These efforts result in the compilation of lists of genes related to diseases and show that an increasing number of diseases is associated with multiple genes. Investigating functional relations among genes associated with the same disease contributes to highlighting molecular mechanisms of the pathogenesis. RESULTS: We present eDGAR, a database collecting and organizing the data on gene/disease associations as derived from OMIM, Humsavar and ClinVar. For each disease-associated gene, eDGAR collects information on its annotation. Specifically, for lists of genes, eDGAR provides information on: i) interactions retrieved from PDB, BIOGRID and STRING; ii) co-occurrence in stable and functional structural complexes; iii) shared Gene Ontology annotations; iv) shared KEGG and REACTOME pathways; v) enriched functional annotations computed with NET-GE; vi) regulatory interactions derived from TRRUST; vii) localization on chromosomes and/or co-localisation in neighboring loci. The present release of eDGAR includes 2672 diseases, related to 3658 different genes, for a total number of 5729 gene-disease associations. 71% of the genes are linked to 621 multigenic diseases and eDGAR highlights their common GO terms, KEGG/REACTOME pathways, physical and regulatory interactions. eDGAR includes a network based enrichment method for detecting statistically significant functional terms associated to groups of genes. CONCLUSIONS: eDGAR offers a resource to analyze disease-gene associations. In multigenic diseases genes can share physical interactions and/or co-occurrence in the same functional processes. eDGAR is freely available at: edgar.biocomp.unibo.it ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3911-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-08-11 /pmc/articles/PMC5558190/ /pubmed/28812536 http://dx.doi.org/10.1186/s12864-017-3911-3 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Babbi, Giulia Martelli, Pier Luigi Profiti, Giuseppe Bovo, Samuele Savojardo, Castrense Casadio, Rita eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes |
title | eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes |
title_full | eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes |
title_fullStr | eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes |
title_full_unstemmed | eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes |
title_short | eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes |
title_sort | edgar: a database of disease-gene associations with annotated relationships among genes |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5558190/ https://www.ncbi.nlm.nih.gov/pubmed/28812536 http://dx.doi.org/10.1186/s12864-017-3911-3 |
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