TGFBI and neoplasm: Seurat FindMarkers excels at inter-group differential analysis at the single-cell level, efficiently identifying glycollytic-related genes highly expressed in TAN-1 subpopulations; MAST is optimized for sparse sequencing data and excels in detecting differences in low-expression neuroinvasive genes (e.g., TGFBI); DESeq2 is suitable for DEG screening in batch single-cell data and supports multi-group comparisons (e.g., tumor cells at different treatment stages) [62,63].