| URL: | https://www.bgee.org/ |
| Full name: | Bgee database |
| Description: | Bgee is a database to retrieve and compare gene expression patterns in multiple animal species, produced by integrating multiple data types (RNA-Seq, Affymetrix, in situ hybridization, and EST data). It is based exclusively on curated healthy wild-type expression data, to provide a comparable reference of normal gene expression |
| Year founded: | 2007 |
| Last update: | 2023 |
| Version: | 15.1 |
| Accessibility: |
Accessible
|
| Country/Region: | Switzerland |
| University/Institution: | University of Lausanne |
| Address: | Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland. SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland. |
| City: | |
| Province/State: | Lausanne |
| Country/Region: | Switzerland |
| Contact name (PI/Team): | Marc Robinson-Rechavi |
| Contact email (PI/Helpdesk): | bgee@sib.swiss |
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Bgee in 2024: focus on curated single-cell RNA-seq datasets, and query tools. [PMID: 39656924]
Bgee (https://www.bgee.org/) is a database to retrieve and compare gene expression patterns in multiple animal species. Expression data are integrated and made comparable between species thanks to consistent data annotation and processing. In the past years, we have integrated single-cell RNA-sequencing expression data into Bgee through careful curation of public datasets in multiple species. We have fully integrated this new technology along with the wealth of other data existing in Bgee. As a result, Bgee can now provide one definitive answer all the way to the cell resolution about a gene's expression pattern, comparable between species. We have updated our programmatic access tools to adapt to these changes accordingly. We have introduced a new web interface, providing detailed access to our annotations and expression data. It enables users to retrieve data, e.g. for specific organs, cell types or developmental stages, and leverages ontology reasoning to build powerful queries. Finally, we have expanded our species count from 29 to 52, emphasizing fish species critical for vertebrate genome studies, species of agronomic and veterinary importance and nonhuman primates. |
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The Bgee suite: integrated curated expression atlas and comparative transcriptomics in animals. [PMID: 33037820]
Bgee is a database to retrieve and compare gene expression patterns in multiple animal species, produced by integrating multiple data types (RNA-Seq, Affymetrix, in situ hybridization, and EST data). It is based exclusively on curated healthy wild-type expression data (e.g., no gene knock-out, no treatment, no disease), to provide a comparable reference of normal gene expression. Curation includes very large datasets such as GTEx (re-annotation of samples as 'healthy' or not) as well as many small ones. Data are integrated and made comparable between species thanks to consistent data annotation and processing, and to calls of presence/absence of expression, along with expression scores. As a result, Bgee is capable of detecting the conditions of expression of any single gene, accommodating any data type and species. Bgee provides several tools for analyses, allowing, e.g., automated comparisons of gene expression patterns within and between species, retrieval of the prefered conditions of expression of any gene, or enrichment analyses of conditions with expression of sets of genes. Bgee release 14.1 includes 29 animal species, and is available at https://bgee.org/ and through its Bioconductor R package BgeeDB. |
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What to compare and how: Comparative transcriptomics for Evo-Devo. [PMID: 25864439]
Evolutionary developmental biology has grown historically from the capacity to relate patterns of evolution in anatomy to patterns of evolution of expression of specific genes, whether between very distantly related species, or very closely related species or populations. Scaling up such studies by taking advantage of modern transcriptomics brings promising improvements, allowing us to estimate the overall impact and molecular mechanisms of convergence, constraint or innovation in anatomy and development. But it also presents major challenges, including the computational definitions of anatomical homology and of organ function, the criteria for the comparison of developmental stages, the annotation of transcriptomics data to proper anatomical and developmental terms, and the statistical methods to compare transcriptomic data between species to highlight significant conservation or changes. In this article, we review these challenges, and the ongoing efforts to address them, which are emerging from bioinformatics work on ontologies, evolutionary statistics, and data curation, with a focus on their implementation in the context of the development of our database Bgee (http://bgee.org). |