Abstract
MOTIVATION: Understanding age-related transcriptional changes in human tissues is crucial for elucidating molecular mechanisms of aging and disease. Current genomic analysis tools often require programming expertise, limiting accessibility for comprehensive aging studies. Here, we present Age Effect Explorer, an interactive R Shiny application for systematically analyzing age- and sex-related gene expression pattern changes across 54 human tissues using Genotype-Tissue Expression (GTEx) v10 data. RESULTS: We obtained gene-level expression profiles from 981 individuals, and fitted ordinary least squares linear models including age, sex, and technical covariates with FDR correction. Pre-calculated results are stored in a cloud database enabling rapid, code-free exploration through an intuitive web interface. Age Effect Explorer validated known aging markers including age-correlated EDA2R. This resource democratizes access to aging transcriptomics, facilitating the discovery of tissue-specific aging mechanisms. AVAILABILITY AND IMPLEMENTATION: The Age Effect Explorer can be accessed using a web browser at https://menghui.shinyapps.io/ageeffectexplorer/. The code used to create the Shiny application, along with a tutorial, can be found on GitHub at https://github.com/ML198/GTEx-Explorer.