The review dissects the computational workflows, strengths, limitations, and future directions of both technologies. It emphasizes that bulk RNA-seq remains the most cost-effective and robust method for analyzing gene expression across large sample sizes—ideal for clinical cohorts, agricultural populations, and time-series studies. In contrast, scRNA-seq offers unprecedented resolution, enabling scientists to uncover cellular heterogeneity, identify rare cell types, and trace developmental trajectories at the single-cell level.
