TY - JOUR
T1 - GENI
T2 - A web server to identify gene set enrichments in tumor samples
AU - Hayashi, Arata
AU - Ruppo, Shmuel
AU - Heilbrun, Elisheva E.
AU - Mazzoni, Chiara
AU - Adar, Sheera
AU - Yassour, Moran
AU - Rmaileh, Areej Abu
AU - Shaul, Yoav D.
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/1
Y1 - 2023/1
N2 - 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.
AB - 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.
KW - Bioinformatics
KW - Cancer biology
KW - Cancer-associated molecular mechanisms
KW - Clinical data
KW - Gene Set Enrichment Analysis
KW - Multi-Gene Analysis
KW - TCGA
KW - Tumor samples
KW - Web-based tools
UR - http://www.scopus.com/inward/record.url?scp=85176284329&partnerID=8YFLogxK
U2 - 10.1016/j.csbj.2023.10.053
DO - 10.1016/j.csbj.2023.10.053
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C2 - 38034403
AN - SCOPUS:85176284329
SN - 2001-0370
VL - 21
SP - 5531
EP - 5537
JO - Computational and Structural Biotechnology Journal
JF - Computational and Structural Biotechnology Journal
ER -
