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GENI: A web server to identify gene set enrichments in tumor samples

The Cancer Genome Atlas (TCGA) and analogous projects have yielded invaluable tumor-associated genomic data. Despite several web-based platforms designed to enhance accessibility, certain analyses require prior bioinformatic expertise. To address this need, we developed Gene ENrichment Identifier (G...

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Autores principales: Hayashi, Arata, Ruppo, Shmuel, Heilbrun, Elisheva E., Mazzoni, Chiara, Adar, Sheera, Yassour, Moran, Rmaileh, Areej Abu, Shaul, Yoav D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10681878/
https://www.ncbi.nlm.nih.gov/pubmed/38034403
http://dx.doi.org/10.1016/j.csbj.2023.10.053
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author Hayashi, Arata
Ruppo, Shmuel
Heilbrun, Elisheva E.
Mazzoni, Chiara
Adar, Sheera
Yassour, Moran
Rmaileh, Areej Abu
Shaul, Yoav D.
author_facet Hayashi, Arata
Ruppo, Shmuel
Heilbrun, Elisheva E.
Mazzoni, Chiara
Adar, Sheera
Yassour, Moran
Rmaileh, Areej Abu
Shaul, Yoav D.
author_sort Hayashi, Arata
collection PubMed
description The Cancer Genome Atlas (TCGA) and analogous projects have yielded invaluable tumor-associated genomic data. Despite several web-based platforms designed to enhance accessibility, certain analyses require prior bioinformatic expertise. To address this need, we developed Gene ENrichment Identifier (GENI, https://www.shaullab.com/geni), which is designed to promptly compute correlations for genes of interest against the entire transcriptome and rank them against well-established biological gene sets. Additionally, it generates comprehensive tables containing genes of interest and their corresponding correlation coefficients, presented in publication-quality graphs. Furthermore, GENI has the capability to analyze multiple genes simultaneously within a given gene set, elucidating their significance within a specific biological context. Overall, GENI's user-friendly interface simplifies the biological interpretation and analysis of cancer patient-associated data, advancing the understanding of cancer biology and accelerating scientific discoveries.
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spelling pubmed-106818782023-11-30 GENI: A web server to identify gene set enrichments in tumor samples Hayashi, Arata Ruppo, Shmuel Heilbrun, Elisheva E. Mazzoni, Chiara Adar, Sheera Yassour, Moran Rmaileh, Areej Abu Shaul, Yoav D. Comput Struct Biotechnol J Software/Web Server Article The Cancer Genome Atlas (TCGA) and analogous projects have yielded invaluable tumor-associated genomic data. Despite several web-based platforms designed to enhance accessibility, certain analyses require prior bioinformatic expertise. To address this need, we developed Gene ENrichment Identifier (GENI, https://www.shaullab.com/geni), which is designed to promptly compute correlations for genes of interest against the entire transcriptome and rank them against well-established biological gene sets. Additionally, it generates comprehensive tables containing genes of interest and their corresponding correlation coefficients, presented in publication-quality graphs. Furthermore, GENI has the capability to analyze multiple genes simultaneously within a given gene set, elucidating their significance within a specific biological context. Overall, GENI's user-friendly interface simplifies the biological interpretation and analysis of cancer patient-associated data, advancing the understanding of cancer biology and accelerating scientific discoveries. Research Network of Computational and Structural Biotechnology 2023-10-31 /pmc/articles/PMC10681878/ /pubmed/38034403 http://dx.doi.org/10.1016/j.csbj.2023.10.053 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Software/Web Server Article
Hayashi, Arata
Ruppo, Shmuel
Heilbrun, Elisheva E.
Mazzoni, Chiara
Adar, Sheera
Yassour, Moran
Rmaileh, Areej Abu
Shaul, Yoav D.
GENI: A web server to identify gene set enrichments in tumor samples
title GENI: A web server to identify gene set enrichments in tumor samples
title_full GENI: A web server to identify gene set enrichments in tumor samples
title_fullStr GENI: A web server to identify gene set enrichments in tumor samples
title_full_unstemmed GENI: A web server to identify gene set enrichments in tumor samples
title_short GENI: A web server to identify gene set enrichments in tumor samples
title_sort geni: a web server to identify gene set enrichments in tumor samples
topic Software/Web Server Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10681878/
https://www.ncbi.nlm.nih.gov/pubmed/38034403
http://dx.doi.org/10.1016/j.csbj.2023.10.053
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