This study introduces a scalable Perturb-seq workflow to systematically identify the targets of signaling regulators across diverse biological contexts. The authors performed over 1,500 perturbations across six cell lines and five biological signaling contexts, using a combination of CRISPR interference (CRISPRi) and single-cell RNA sequencing (scRNA-seq). They developed an improved computational framework, Mixscale, to address cellular variation in perturbation efficiency and optimized statistical methods to learn differentially expressed gene (DEG) lists and conserved molecular signatures. The study demonstrates that Perturb-seq-derived gene lists can be used to infer changes in signaling pathway activation for in-vivo and in-situ samples, enhancing our understanding of signaling regulators and their targets. The work lays a computational framework for the systematic construction of an 'atlas' of perturbation signatures, which can be applied to various biological contexts and cellular processes to identify additional gene signatures.This study introduces a scalable Perturb-seq workflow to systematically identify the targets of signaling regulators across diverse biological contexts. The authors performed over 1,500 perturbations across six cell lines and five biological signaling contexts, using a combination of CRISPR interference (CRISPRi) and single-cell RNA sequencing (scRNA-seq). They developed an improved computational framework, Mixscale, to address cellular variation in perturbation efficiency and optimized statistical methods to learn differentially expressed gene (DEG) lists and conserved molecular signatures. The study demonstrates that Perturb-seq-derived gene lists can be used to infer changes in signaling pathway activation for in-vivo and in-situ samples, enhancing our understanding of signaling regulators and their targets. The work lays a computational framework for the systematic construction of an 'atlas' of perturbation signatures, which can be applied to various biological contexts and cellular processes to identify additional gene signatures.