Publication | Open Access
GENI: A web server to identify gene set enrichments in tumor samples
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Citations
21
References
2023
Year
EngineeringGeneticsPathologyGenomicsBioinformatics DatabaseGene Expression ProfilingTumor BiologyTumor HeterogeneityMultiple GenesAnalogous ProjectsBiostatisticsGene Enrichment IdentifierMolecular DiagnosticsMicroarray Data AnalysisCancer ResearchTranslational BioinformaticsBiological DatabaseStatistical GeneticsOmicsPathway AnalysisWeb ServerFunctional GenomicsBioinformaticsTumor SamplesComputational BiologyCancer GenomicsSystems BiologyMedicine
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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