A visualization tool for individual gene expression profiles among males and females in GTEx tissues

Sexual dimorphism has been implied to certain human physiology and diseases. This topic has recently garnered more attention, highlighting individual variances in precision medicine and individualized clinical trials. It is recognized that individual gene expression variations in males and females could have profound physiological impacts. Tissue specific expression profiles determine protein-coding gene activities and contribute additional physiological variations. Therefore, tissue specific gene expression profiles should be comprehensively analyzed among individual human subjects. In this report, we developed a user-friendly bioinformatic tool to visualize gene expression levels and variances across tissue samples, aiming to facilitate research into potential sexual dimorphism genes. The Gini coefficient metric was used with the most recent GTEx V10 datasets to examine variations in the expression profiles of human protein-coding genes across 43 tissue subtypes. Next, these variations were specifically evaluated using the Gini coefficient index for male and female individuals across all tissue subtypes. Our web-based visualization tool generated tissue specific expression profiles for individual male and female samples. It concurrently illustrates expression levels and variation comparisons between male and female groups across all tissue subtypes. Although most protein-coding genes had similar expression variation patterns between the two sexes, several genes exhibited distinct variations for some tissue subtypes, as indicated by their significant Z-scores in Gini index disparities. Users can explore differentially expressed protein-coding genes across tissue subtypes or search for genes of interest in the Tissue Prominent Sexual Dimorphism Gene database ( https://tpsdg.ibms.sinica.edu.tw ). This database can be employed to visualize expression levels and variations among individual samples within specific tissues, thereby facilitating future research into divergently expressed protein-coding genes in the human population.