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ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions
Reference datasets are often used to compare, interpret or validate experimental data and analytical methods. In the field of gene expression, several reference datasets have been published. Typically, they consist of individual baseline or spike-in experiments carried out in a single laboratory and...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165432/ https://www.ncbi.nlm.nih.gov/pubmed/25228922 http://dx.doi.org/10.1186/1756-0381-7-18 |
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author | Zimmermann, Philip Bleuler, Stefan Laule, Oliver Martin, Florian Ivanov, Nikolai V Campanoni, Prisca Oishi, Karen Lugon-Moulin, Nicolas Wyss, Markus Hruz, Tomas Gruissem, Wilhelm |
author_facet | Zimmermann, Philip Bleuler, Stefan Laule, Oliver Martin, Florian Ivanov, Nikolai V Campanoni, Prisca Oishi, Karen Lugon-Moulin, Nicolas Wyss, Markus Hruz, Tomas Gruissem, Wilhelm |
author_sort | Zimmermann, Philip |
collection | PubMed |
description | Reference datasets are often used to compare, interpret or validate experimental data and analytical methods. In the field of gene expression, several reference datasets have been published. Typically, they consist of individual baseline or spike-in experiments carried out in a single laboratory and representing a particular set of conditions. Here, we describe a new type of standardized datasets representative for the spatial and temporal dimensions of gene expression. They result from integrating expression data from a large number of globally normalized and quality controlled public experiments. Expression data is aggregated by anatomical part or stage of development to yield a representative transcriptome for each category. For example, we created a genome-wide expression dataset representing the FDA tissue panel across 35 tissue types. The proposed datasets were created for human and several model organisms and are publicly available at http://www.expressiondata.org. |
format | Online Article Text |
id | pubmed-4165432 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41654322014-09-17 ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions Zimmermann, Philip Bleuler, Stefan Laule, Oliver Martin, Florian Ivanov, Nikolai V Campanoni, Prisca Oishi, Karen Lugon-Moulin, Nicolas Wyss, Markus Hruz, Tomas Gruissem, Wilhelm BioData Min Software Article Reference datasets are often used to compare, interpret or validate experimental data and analytical methods. In the field of gene expression, several reference datasets have been published. Typically, they consist of individual baseline or spike-in experiments carried out in a single laboratory and representing a particular set of conditions. Here, we describe a new type of standardized datasets representative for the spatial and temporal dimensions of gene expression. They result from integrating expression data from a large number of globally normalized and quality controlled public experiments. Expression data is aggregated by anatomical part or stage of development to yield a representative transcriptome for each category. For example, we created a genome-wide expression dataset representing the FDA tissue panel across 35 tissue types. The proposed datasets were created for human and several model organisms and are publicly available at http://www.expressiondata.org. BioMed Central 2014-08-31 /pmc/articles/PMC4165432/ /pubmed/25228922 http://dx.doi.org/10.1186/1756-0381-7-18 Text en Copyright © 2014 Zimmermann et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. |
spellingShingle | Software Article Zimmermann, Philip Bleuler, Stefan Laule, Oliver Martin, Florian Ivanov, Nikolai V Campanoni, Prisca Oishi, Karen Lugon-Moulin, Nicolas Wyss, Markus Hruz, Tomas Gruissem, Wilhelm ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions |
title | ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions |
title_full | ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions |
title_fullStr | ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions |
title_full_unstemmed | ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions |
title_short | ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions |
title_sort | expressiondata - a public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions |
topic | Software Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165432/ https://www.ncbi.nlm.nih.gov/pubmed/25228922 http://dx.doi.org/10.1186/1756-0381-7-18 |
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