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Expression Atlas update: from tissues to single cells
Expression Atlas is EMBL-EBI’s resource for gene and protein expression. It sources and compiles data on the abundance and localisation of RNA and proteins in various biological systems and contexts and provides open access to this data for the research community. With the increased availability of...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145605/ https://www.ncbi.nlm.nih.gov/pubmed/31665515 http://dx.doi.org/10.1093/nar/gkz947 |
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author | Papatheodorou, Irene Moreno, Pablo Manning, Jonathan Fuentes, Alfonso Muñoz-Pomer George, Nancy Fexova, Silvie Fonseca, Nuno A Füllgrabe, Anja Green, Matthew Huang, Ni Huerta, Laura Iqbal, Haider Jianu, Monica Mohammed, Suhaib Zhao, Lingyun Jarnuczak, Andrew F Jupp, Simon Marioni, John Meyer, Kerstin Petryszak, Robert Prada Medina, Cesar Augusto Talavera-López, Carlos Teichmann, Sarah Vizcaino, Juan Antonio Brazma, Alvis |
author_facet | Papatheodorou, Irene Moreno, Pablo Manning, Jonathan Fuentes, Alfonso Muñoz-Pomer George, Nancy Fexova, Silvie Fonseca, Nuno A Füllgrabe, Anja Green, Matthew Huang, Ni Huerta, Laura Iqbal, Haider Jianu, Monica Mohammed, Suhaib Zhao, Lingyun Jarnuczak, Andrew F Jupp, Simon Marioni, John Meyer, Kerstin Petryszak, Robert Prada Medina, Cesar Augusto Talavera-López, Carlos Teichmann, Sarah Vizcaino, Juan Antonio Brazma, Alvis |
author_sort | Papatheodorou, Irene |
collection | PubMed |
description | Expression Atlas is EMBL-EBI’s resource for gene and protein expression. It sources and compiles data on the abundance and localisation of RNA and proteins in various biological systems and contexts and provides open access to this data for the research community. With the increased availability of single cell RNA-Seq datasets in the public archives, we have now extended Expression Atlas with a new added-value service to display gene expression in single cells. Single Cell Expression Atlas was launched in 2018 and currently includes 123 single cell RNA-Seq studies from 12 species. The website can be searched by genes within or across species to reveal experiments, tissues and cell types where this gene is expressed or under which conditions it is a marker gene. Within each study, cells can be visualized using a pre-calculated t-SNE plot and can be coloured by different features or by cell clusters based on gene expression. Within each experiment, there are links to downloadable files, such as RNA quantification matrices, clustering results, reports on protocols and associated metadata, such as assigned cell types. |
format | Online Article Text |
id | pubmed-7145605 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-71456052020-04-13 Expression Atlas update: from tissues to single cells Papatheodorou, Irene Moreno, Pablo Manning, Jonathan Fuentes, Alfonso Muñoz-Pomer George, Nancy Fexova, Silvie Fonseca, Nuno A Füllgrabe, Anja Green, Matthew Huang, Ni Huerta, Laura Iqbal, Haider Jianu, Monica Mohammed, Suhaib Zhao, Lingyun Jarnuczak, Andrew F Jupp, Simon Marioni, John Meyer, Kerstin Petryszak, Robert Prada Medina, Cesar Augusto Talavera-López, Carlos Teichmann, Sarah Vizcaino, Juan Antonio Brazma, Alvis Nucleic Acids Res Database Issue Expression Atlas is EMBL-EBI’s resource for gene and protein expression. It sources and compiles data on the abundance and localisation of RNA and proteins in various biological systems and contexts and provides open access to this data for the research community. With the increased availability of single cell RNA-Seq datasets in the public archives, we have now extended Expression Atlas with a new added-value service to display gene expression in single cells. Single Cell Expression Atlas was launched in 2018 and currently includes 123 single cell RNA-Seq studies from 12 species. The website can be searched by genes within or across species to reveal experiments, tissues and cell types where this gene is expressed or under which conditions it is a marker gene. Within each study, cells can be visualized using a pre-calculated t-SNE plot and can be coloured by different features or by cell clusters based on gene expression. Within each experiment, there are links to downloadable files, such as RNA quantification matrices, clustering results, reports on protocols and associated metadata, such as assigned cell types. Oxford University Press 2020-01-08 2019-10-30 /pmc/articles/PMC7145605/ /pubmed/31665515 http://dx.doi.org/10.1093/nar/gkz947 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Issue Papatheodorou, Irene Moreno, Pablo Manning, Jonathan Fuentes, Alfonso Muñoz-Pomer George, Nancy Fexova, Silvie Fonseca, Nuno A Füllgrabe, Anja Green, Matthew Huang, Ni Huerta, Laura Iqbal, Haider Jianu, Monica Mohammed, Suhaib Zhao, Lingyun Jarnuczak, Andrew F Jupp, Simon Marioni, John Meyer, Kerstin Petryszak, Robert Prada Medina, Cesar Augusto Talavera-López, Carlos Teichmann, Sarah Vizcaino, Juan Antonio Brazma, Alvis Expression Atlas update: from tissues to single cells |
title | Expression Atlas update: from tissues to single cells |
title_full | Expression Atlas update: from tissues to single cells |
title_fullStr | Expression Atlas update: from tissues to single cells |
title_full_unstemmed | Expression Atlas update: from tissues to single cells |
title_short | Expression Atlas update: from tissues to single cells |
title_sort | expression atlas update: from tissues to single cells |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145605/ https://www.ncbi.nlm.nih.gov/pubmed/31665515 http://dx.doi.org/10.1093/nar/gkz947 |
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