Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations

The identification of genetic and chemical perturbations with similar impacts on cell morphology can elucidate compounds' mechanisms of action or novel regulators of genetic pathways. Research on methods for identifying such similarities has lagged due to a lack of carefully designed and well-annotated image sets of cells treated with chemical and genetic perturbations. Here we create such a Resource dataset, CPJUMP1, in which each perturbed gene's product is a known target of at least two chemical compounds in the dataset. We systematically explore the directionality of correlations among perturbations that target the same protein encoded by a given gene, and we find that identifying matches between chemical…

• SV
  Silicon Valley Community Foundation

  Award: 2020-225720
• ML
  Massachusetts Life Sciences Center
• BI
  Broad Institute

  Award: OD-026839-01
• NI
  National Institutes of Health

  Awards: MIRA R35 GM122547, 2020-225720, OD-026839-01, NIH MIRA R35 GM122547, R35 GM122547