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Enrichr: a comprehensive gene set enrichment analysis web server 2016 update
Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and downloa...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987924/ https://www.ncbi.nlm.nih.gov/pubmed/27141961 http://dx.doi.org/10.1093/nar/gkw377 |
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author | Kuleshov, Maxim V. Jones, Matthew R. Rouillard, Andrew D. Fernandez, Nicolas F. Duan, Qiaonan Wang, Zichen Koplev, Simon Jenkins, Sherry L. Jagodnik, Kathleen M. Lachmann, Alexander McDermott, Michael G. Monteiro, Caroline D. Gundersen, Gregory W. Ma'ayan, Avi |
author_facet | Kuleshov, Maxim V. Jones, Matthew R. Rouillard, Andrew D. Fernandez, Nicolas F. Duan, Qiaonan Wang, Zichen Koplev, Simon Jenkins, Sherry L. Jagodnik, Kathleen M. Lachmann, Alexander McDermott, Michael G. Monteiro, Caroline D. Gundersen, Gregory W. Ma'ayan, Avi |
author_sort | Kuleshov, Maxim V. |
collection | PubMed |
description | Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr. |
format | Online Article Text |
id | pubmed-4987924 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-49879242016-08-22 Enrichr: a comprehensive gene set enrichment analysis web server 2016 update Kuleshov, Maxim V. Jones, Matthew R. Rouillard, Andrew D. Fernandez, Nicolas F. Duan, Qiaonan Wang, Zichen Koplev, Simon Jenkins, Sherry L. Jagodnik, Kathleen M. Lachmann, Alexander McDermott, Michael G. Monteiro, Caroline D. Gundersen, Gregory W. Ma'ayan, Avi Nucleic Acids Res Web Server issue Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr. Oxford University Press 2016-07-08 2016-05-03 /pmc/articles/PMC4987924/ /pubmed/27141961 http://dx.doi.org/10.1093/nar/gkw377 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server issue Kuleshov, Maxim V. Jones, Matthew R. Rouillard, Andrew D. Fernandez, Nicolas F. Duan, Qiaonan Wang, Zichen Koplev, Simon Jenkins, Sherry L. Jagodnik, Kathleen M. Lachmann, Alexander McDermott, Michael G. Monteiro, Caroline D. Gundersen, Gregory W. Ma'ayan, Avi Enrichr: a comprehensive gene set enrichment analysis web server 2016 update |
title | Enrichr: a comprehensive gene set enrichment analysis web server 2016 update |
title_full | Enrichr: a comprehensive gene set enrichment analysis web server 2016 update |
title_fullStr | Enrichr: a comprehensive gene set enrichment analysis web server 2016 update |
title_full_unstemmed | Enrichr: a comprehensive gene set enrichment analysis web server 2016 update |
title_short | Enrichr: a comprehensive gene set enrichment analysis web server 2016 update |
title_sort | enrichr: a comprehensive gene set enrichment analysis web server 2016 update |
topic | Web Server issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987924/ https://www.ncbi.nlm.nih.gov/pubmed/27141961 http://dx.doi.org/10.1093/nar/gkw377 |
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