This project uses high-throughput screening and multi-omics analysis to investigate small-molecule-driven reprogramming of cancer cells toward an antigen-presenting dendritic-cell-like state and its impact on anti-tumor immunity. The computational work will focus on bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics, and ATAC-seq data from mouse and human cancer models, primary tumor samples, and in vivo experiments. The analyses will be used to characterize transcriptional identity, chromatin accessibility, pathway activity, cellular heterogeneity, and spatial immune organization during reprogramming. High-performance computing is required for quality control, alignment, quantification, differential analysis, clustering, multi-sample integration, trajectory inference, peak calling, motif analysis, and transcriptomic/epigenomic integration. These analyses are necessary to identify molecular signatures of successful reprogramming and to support mechanistic interpretation and prioritization of experimental conditions.