Exploration of cancer cell states in spatial transcriptomics data
cancer
CANCER
Based on the deconvolution results, the spots with highly abundant malignant cells (fraction > 0.7) were selected to carry out clustering analysis. The optimal number of clusters (i.e., cancer cell states) was determined by calculating the silhouette value. We then collected 16 cancer gene modules from a recent study