a Main steps in ACTIONet. b ACTION-based matrix decomposition. Dimensionality reduction for feature selection (reduction) is coupled with AA to perform individual-level decomposition and identify k latent cell-state patterns (archetypes). A column c of the cell influence matrix C encodes the influence of cells on the patterns. A column h of the cell-state encoding matrix H encodes the relative contribution of each pattern to the transcriptome of each cell. c Multilevel ACTION decomposition with an increment in the number of archetypes per level. Concatenation of individual-level matrices defines multilevel encoding (H*), cell influence (C*), and profile matrices (W*). d, e Metric cell space defined by measuring distances on multilevel cell-state encodings. f Construction of a sparse network representation of the cell space.