Populations of cells can be perturbed by various chemical and genetic treatments and the impact on the cells’ gene expression (transcription, i.e. mRNA levels) and morphology (in an image-based assay) can be measured in high dimensions. The patterns observed in this profile data can be used for more than a dozen applications in drug discovery and basic biology research, but both types of profiles are rarely available for large-scale experiments. We provide a collection of four datasets with both gene expression and morphological profile data useful for developing and testing multi-modal methodologies. Roughly a thousand features are measured for each of the two data types, across more than 28,000 thousand chemical and genetic perturbations. We define biological problems that can be investigated using the shared and complementary information in these two data modalities, provide baseline analysis and evaluation metrics for multi-omic applications, and make the data resource publicly available ( http://broad.io/rosetta ).