RNA sequencing (RNA-seq) is a powerful technique for understanding cellular state and dynamics. However, comprehensive transcriptomic characterization of multiple RNA-seq datasets is laborious without bioinformatics training and skills. To remove the barriers to sequence data analysis in the research community, we have developed “RNAseqChef” (RNA-seqdatacontrollerhighlightingexpressionfeatures), a web-based platform of systematic transcriptome analysis that can automatically detect, integrate, and visualize differentially expressed genes and their biological functions. To validate its versatile performance, we examined the pharmacological action of sulforaphane (SFN), a natural isothiocyanate, on various types of cells and mouse tissues using multiple datasetsin vitroandin vivo. Notably, SFN treatment upregulated the ATF6-mediated unfolded protein response in the liver and the NRF2-mediated antioxidant response in the skeletal muscle of diet-induced obese mice. In contrast, the commonly downregulated pathways included collagen synthesis and circadian rhythms in the tissues tested. On the server of RNAseqChef, we simply evaluated and visualized all analyzing data and discovered the NRF2-independent action of SFN. Collectively, RNAseqChef provides an easy-to-use open resource that identifies context-dependent transcriptomic features and standardizes data assessment.