Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2023.04.05.535584v1?rss=1
Authors: Hayashi, A., Ruppo, S., Heilbrun, E. E., Mazzoni, C., Adar, S., Yassour, M., Abu Rmaileh, A., Shaul, Y. D.
Abstract:
The Cancer Genome Atlas (TCGA) and other projects provide informative tumor-associated genomic data for the broad research community. Hence, several useful web-based tools have been generated to ease non-expert users with the analysis and characterization of a specific gene behavior in selected tumors. However, none of the existing tools offer the user the means to evaluate the expression profile of a given gene in the context of the whole transcriptome. Currently, such analyses require prior bioinformatic knowledge and expertise. Therefore, we developed GENI (Gene ENrichment Identifier) as a fast, user-friendly tool to analyze the TCGA expression data for gene set enrichments. GENI analyzes large-scale tumor-associated gene expression datasets and evaluates biological relevance, thus offering researchers a simplified means to analyze cancer patient-derived data.
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