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modEnrichr: a suite of gene set enrichment analysis tools for model organisms

High-throughput experiments produce increasingly large datasets that are difficult to analyze and integrate. While most data integration approaches focus on aligning metadata, data integration can be achieved by abstracting experimental results into gene sets. Such gene sets can be made available fo...

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Autores principales: Kuleshov, Maxim V, Diaz, Jennifer E L, Flamholz, Zachary N, Keenan, Alexandra B, Lachmann, Alexander, Wojciechowicz, Megan L, Cagan, Ross L, Ma’ayan, Avi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602483/
https://www.ncbi.nlm.nih.gov/pubmed/31069376
http://dx.doi.org/10.1093/nar/gkz347
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author Kuleshov, Maxim V
Diaz, Jennifer E L
Flamholz, Zachary N
Keenan, Alexandra B
Lachmann, Alexander
Wojciechowicz, Megan L
Cagan, Ross L
Ma’ayan, Avi
author_facet Kuleshov, Maxim V
Diaz, Jennifer E L
Flamholz, Zachary N
Keenan, Alexandra B
Lachmann, Alexander
Wojciechowicz, Megan L
Cagan, Ross L
Ma’ayan, Avi
author_sort Kuleshov, Maxim V
collection PubMed
description High-throughput experiments produce increasingly large datasets that are difficult to analyze and integrate. While most data integration approaches focus on aligning metadata, data integration can be achieved by abstracting experimental results into gene sets. Such gene sets can be made available for reuse through gene set enrichment analysis tools such as Enrichr. Enrichr currently only supports gene sets compiled from human and mouse, limiting accessibility for investigators that study other model organisms. modEnrichr is an expansion of Enrichr for four model organisms: fish, fly, worm and yeast. The gene set libraries within FishEnrichr, FlyEnrichr, WormEnrichr and YeastEnrichr are created from the Gene Ontology, mRNA expression profiles, GeneRIF, pathway databases, protein domain databases and other organism-specific resources. Additionally, libraries were created by predicting gene function from RNA-seq co-expression data processed uniformly from the gene expression omnibus for each organism. The modEnrichr suite of tools provides the ability to convert gene lists across species using an ortholog conversion tool that automatically detects the species. For complex analyses, modEnrichr provides API access that enables submitting batch queries. In summary, modEnrichr leverages existing model organism databases and other resources to facilitate comprehensive hypothesis generation through data integration.
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spelling pubmed-66024832019-07-05 modEnrichr: a suite of gene set enrichment analysis tools for model organisms Kuleshov, Maxim V Diaz, Jennifer E L Flamholz, Zachary N Keenan, Alexandra B Lachmann, Alexander Wojciechowicz, Megan L Cagan, Ross L Ma’ayan, Avi Nucleic Acids Res Web Server Issue High-throughput experiments produce increasingly large datasets that are difficult to analyze and integrate. While most data integration approaches focus on aligning metadata, data integration can be achieved by abstracting experimental results into gene sets. Such gene sets can be made available for reuse through gene set enrichment analysis tools such as Enrichr. Enrichr currently only supports gene sets compiled from human and mouse, limiting accessibility for investigators that study other model organisms. modEnrichr is an expansion of Enrichr for four model organisms: fish, fly, worm and yeast. The gene set libraries within FishEnrichr, FlyEnrichr, WormEnrichr and YeastEnrichr are created from the Gene Ontology, mRNA expression profiles, GeneRIF, pathway databases, protein domain databases and other organism-specific resources. Additionally, libraries were created by predicting gene function from RNA-seq co-expression data processed uniformly from the gene expression omnibus for each organism. The modEnrichr suite of tools provides the ability to convert gene lists across species using an ortholog conversion tool that automatically detects the species. For complex analyses, modEnrichr provides API access that enables submitting batch queries. In summary, modEnrichr leverages existing model organism databases and other resources to facilitate comprehensive hypothesis generation through data integration. Oxford University Press 2019-07-02 2019-05-09 /pmc/articles/PMC6602483/ /pubmed/31069376 http://dx.doi.org/10.1093/nar/gkz347 Text en © The Author(s) 2019. 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 Non-Commercial 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
Diaz, Jennifer E L
Flamholz, Zachary N
Keenan, Alexandra B
Lachmann, Alexander
Wojciechowicz, Megan L
Cagan, Ross L
Ma’ayan, Avi
modEnrichr: a suite of gene set enrichment analysis tools for model organisms
title modEnrichr: a suite of gene set enrichment analysis tools for model organisms
title_full modEnrichr: a suite of gene set enrichment analysis tools for model organisms
title_fullStr modEnrichr: a suite of gene set enrichment analysis tools for model organisms
title_full_unstemmed modEnrichr: a suite of gene set enrichment analysis tools for model organisms
title_short modEnrichr: a suite of gene set enrichment analysis tools for model organisms
title_sort modenrichr: a suite of gene set enrichment analysis tools for model organisms
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602483/
https://www.ncbi.nlm.nih.gov/pubmed/31069376
http://dx.doi.org/10.1093/nar/gkz347
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