Increasing the number of measured dimensions of tumor-infiltrating DC states. Computational tools can predict multiple dimensions of tumor-infiltrating DC states from single-cell transcriptomes such as fate potential (trajectory inference and RNA velocity), cell–cell interactions, and downstream targets of these ligand–receptor cell–cell interactions (ligand–target modeling), active transcription factors and signaling pathways (transcription factor–target and pathway–target modeling), and conservation of DC states (meta-analyses as performed in this review). These computational prediction tools are instrumental to generate testable hypotheses about tumor-infiltrating DC states; however, multimodal approaches that measure both single-cell transcriptomes and other dimensions are emerging. Available and emerging tools permit the evaluation of other intrinsic features of cells, their location, origins, fate, and functions. *, tools applicable to exploratory models only; GEMM, genetically engineered mouse model.