Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations.
Journal
Nature methods
ISSN: 1548-7105
Titre abrégé: Nat Methods
Pays: United States
ID NLM: 101215604
Informations de publication
Date de publication:
09 Apr 2024
09 Apr 2024
Historique:
received:
23
05
2023
accepted:
11
03
2024
medline:
10
4
2024
pubmed:
10
4
2024
entrez:
9
4
2024
Statut:
aheadofprint
Résumé
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 and genetic perturbations is a challenging task. Our dataset and baseline analyses provide a benchmark for evaluating methods that measure perturbation similarities and impact, and more generally, learn effective representations of cellular state from microscopy images. Such advancements would accelerate the applications of image-based profiling of cellular states, such as uncovering drug mode of action or probing functional genomics.
Identifiants
pubmed: 38594452
doi: 10.1038/s41592-024-02241-6
pii: 10.1038/s41592-024-02241-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : U.S. Department of Health & Human Services | National Institutes of Health (NIH)
ID : NIH MIRA R35 GM122547
Informations de copyright
© 2024. The Author(s).
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