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netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis

Existing software tools for topology-based pathway enrichment analysis are either computationally inefficient, have undesirable statistical power, or require expert knowledge to leverage the methods’ capabilities. To address these limitations, we have overhauled NetGSA, an existing topology-based me...

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Detalles Bibliográficos
Autores principales: Hellstern, Michael, Ma, Jing, Yue, Kun, Shojaie, Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8221786/
https://www.ncbi.nlm.nih.gov/pubmed/34115744
http://dx.doi.org/10.1371/journal.pcbi.1008979
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author Hellstern, Michael
Ma, Jing
Yue, Kun
Shojaie, Ali
author_facet Hellstern, Michael
Ma, Jing
Yue, Kun
Shojaie, Ali
author_sort Hellstern, Michael
collection PubMed
description Existing software tools for topology-based pathway enrichment analysis are either computationally inefficient, have undesirable statistical power, or require expert knowledge to leverage the methods’ capabilities. To address these limitations, we have overhauled NetGSA, an existing topology-based method, to provide a computationally-efficient user-friendly tool that offers interactive visualization. Pathway enrichment analysis for thousands of genes can be performed in minutes on a personal computer without sacrificing statistical power. The new software also removes the need for expert knowledge by directly curating gene-gene interaction information from multiple external databases. Lastly, by utilizing the capabilities of Cytoscape, the new software also offers interactive and intuitive network visualization.
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spelling pubmed-82217862021-07-07 netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis Hellstern, Michael Ma, Jing Yue, Kun Shojaie, Ali PLoS Comput Biol Research Article Existing software tools for topology-based pathway enrichment analysis are either computationally inefficient, have undesirable statistical power, or require expert knowledge to leverage the methods’ capabilities. To address these limitations, we have overhauled NetGSA, an existing topology-based method, to provide a computationally-efficient user-friendly tool that offers interactive visualization. Pathway enrichment analysis for thousands of genes can be performed in minutes on a personal computer without sacrificing statistical power. The new software also removes the need for expert knowledge by directly curating gene-gene interaction information from multiple external databases. Lastly, by utilizing the capabilities of Cytoscape, the new software also offers interactive and intuitive network visualization. Public Library of Science 2021-06-11 /pmc/articles/PMC8221786/ /pubmed/34115744 http://dx.doi.org/10.1371/journal.pcbi.1008979 Text en © 2021 Hellstern et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hellstern, Michael
Ma, Jing
Yue, Kun
Shojaie, Ali
netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis
title netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis
title_full netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis
title_fullStr netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis
title_full_unstemmed netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis
title_short netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis
title_sort netgsa: fast computation and interactive visualization for topology-based pathway enrichment analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8221786/
https://www.ncbi.nlm.nih.gov/pubmed/34115744
http://dx.doi.org/10.1371/journal.pcbi.1008979
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