Cargando…

Enrichr-KG: bridging enrichment analysis across multiple libraries

Gene and protein set enrichment analysis is a critical step in the analysis of data collected from omics experiments. Enrichr is a popular gene set enrichment analysis web-server search engine that contains hundreds of thousands of annotated gene sets. While Enrichr has been useful in providing enri...

Descripción completa

Detalles Bibliográficos
Autores principales: Evangelista, John Erol, Xie, Zhuorui, Marino, Giacomo B, Nguyen, Nhi, Clarke, Daniel J B, Ma’ayan, Avi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320098/
https://www.ncbi.nlm.nih.gov/pubmed/37166973
http://dx.doi.org/10.1093/nar/gkad393
_version_ 1785068377162645504
author Evangelista, John Erol
Xie, Zhuorui
Marino, Giacomo B
Nguyen, Nhi
Clarke, Daniel J B
Ma’ayan, Avi
author_facet Evangelista, John Erol
Xie, Zhuorui
Marino, Giacomo B
Nguyen, Nhi
Clarke, Daniel J B
Ma’ayan, Avi
author_sort Evangelista, John Erol
collection PubMed
description Gene and protein set enrichment analysis is a critical step in the analysis of data collected from omics experiments. Enrichr is a popular gene set enrichment analysis web-server search engine that contains hundreds of thousands of annotated gene sets. While Enrichr has been useful in providing enrichment analysis with many gene set libraries from different categories, integrating enrichment results across libraries and domains of knowledge can further hypothesis generation. To this end, Enrichr-KG is a knowledge graph database and a web-server application that combines selected gene set libraries from Enrichr for integrative enrichment analysis and visualization. The enrichment results are presented as subgraphs made of nodes and links that connect genes to their enriched terms. In addition, users of Enrichr-KG can add gene-gene links, as well as predicted genes to the subgraphs. This graphical representation of cross-library results with enriched and predicted genes can illuminate hidden associations between genes and annotated enriched terms from across datasets and resources. Enrichr-KG currently serves 26 gene set libraries from different categories that include transcription, pathways, ontologies, diseases/drugs, and cell types. To demonstrate the utility of Enrichr-KG we provide several case studies. Enrichr-KG is freely available at: https://maayanlab.cloud/enrichr-kg.
format Online
Article
Text
id pubmed-10320098
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-103200982023-07-06 Enrichr-KG: bridging enrichment analysis across multiple libraries Evangelista, John Erol Xie, Zhuorui Marino, Giacomo B Nguyen, Nhi Clarke, Daniel J B Ma’ayan, Avi Nucleic Acids Res Web Server Issue Gene and protein set enrichment analysis is a critical step in the analysis of data collected from omics experiments. Enrichr is a popular gene set enrichment analysis web-server search engine that contains hundreds of thousands of annotated gene sets. While Enrichr has been useful in providing enrichment analysis with many gene set libraries from different categories, integrating enrichment results across libraries and domains of knowledge can further hypothesis generation. To this end, Enrichr-KG is a knowledge graph database and a web-server application that combines selected gene set libraries from Enrichr for integrative enrichment analysis and visualization. The enrichment results are presented as subgraphs made of nodes and links that connect genes to their enriched terms. In addition, users of Enrichr-KG can add gene-gene links, as well as predicted genes to the subgraphs. This graphical representation of cross-library results with enriched and predicted genes can illuminate hidden associations between genes and annotated enriched terms from across datasets and resources. Enrichr-KG currently serves 26 gene set libraries from different categories that include transcription, pathways, ontologies, diseases/drugs, and cell types. To demonstrate the utility of Enrichr-KG we provide several case studies. Enrichr-KG is freely available at: https://maayanlab.cloud/enrichr-kg. Oxford University Press 2023-05-11 /pmc/articles/PMC10320098/ /pubmed/37166973 http://dx.doi.org/10.1093/nar/gkad393 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://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
Evangelista, John Erol
Xie, Zhuorui
Marino, Giacomo B
Nguyen, Nhi
Clarke, Daniel J B
Ma’ayan, Avi
Enrichr-KG: bridging enrichment analysis across multiple libraries
title Enrichr-KG: bridging enrichment analysis across multiple libraries
title_full Enrichr-KG: bridging enrichment analysis across multiple libraries
title_fullStr Enrichr-KG: bridging enrichment analysis across multiple libraries
title_full_unstemmed Enrichr-KG: bridging enrichment analysis across multiple libraries
title_short Enrichr-KG: bridging enrichment analysis across multiple libraries
title_sort enrichr-kg: bridging enrichment analysis across multiple libraries
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320098/
https://www.ncbi.nlm.nih.gov/pubmed/37166973
http://dx.doi.org/10.1093/nar/gkad393
work_keys_str_mv AT evangelistajohnerol enrichrkgbridgingenrichmentanalysisacrossmultiplelibraries
AT xiezhuorui enrichrkgbridgingenrichmentanalysisacrossmultiplelibraries
AT marinogiacomob enrichrkgbridgingenrichmentanalysisacrossmultiplelibraries
AT nguyennhi enrichrkgbridgingenrichmentanalysisacrossmultiplelibraries
AT clarkedanieljb enrichrkgbridgingenrichmentanalysisacrossmultiplelibraries
AT maayanavi enrichrkgbridgingenrichmentanalysisacrossmultiplelibraries