scSemiProfiler is an innovative computational tool that combines deep generative models and active learning to economically generate single-cell data for biological studies. It supports two main application scenarios: semi-profiling, which uses deep generative learning and active learning to generate a single-cell cohort with 1/10 to 1/3 sequencing cost, and single-cell level deconvolution, which generates single-cell data from bulk data and single-cell references. For more insights, check out our manuscript in Nature Communications, and please consider citing it if you find our method beneficial.