Scperturb: Harmonized Single-Cell Perturbation Data

Recent biotechnological advances led to growing numbers of single-cell studies, which reveal molecular and phenotypic responses to large numbers of perturbations. However, analysis across diverse datasets is typically hampered by differences in format, naming conventions, data filtering and normalization. In order to facilitate development and benchmarking of computational methods in systems biology, we collect a set of 44 publicly available single-cell perturbation-response datasets with molecular readouts, including transcriptomics, proteomics and epigenomics. We apply uniform pre-processing and quality control pipelines and harmonize feature annotations. The resulting information resource enables efficient development and testing of computational analysis methods, and facilitates direct comparison and integration across datasets. Using these datasets, we demonstrate the application of E-distance for quantifying perturbation similarity and strength. This work provides an information resource and guide for researchers working with single-cell perturbation data and highlights conceptual considerations for new experiments. The data is publicly available at scperturb.org.