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J Biomol Screen DOI:10.1177/1087057113503553

Comparison of methods for image-based profiling of cellular morphological responses to small-molecule treatment.

Publication TypeJournal Article
Year of Publication2013
AuthorsLjosa, V, Caie, PD, Horst, RTer, Sokolnicki, KL, Jenkins, EL, Daya, S, Roberts, ME, Jones, TR, Singh, S, Genovesio, A, Clemons, PA, Carragher, NO, Carpenter, AE
JournalJ Biomol Screen
Date Published2013 Dec
KeywordsCell Shape, Drug Evaluation, Preclinical, Factor Analysis, Statistical, Humans, MCF-7 Cells, Microscopy, Fluorescence, Phenotype, Small Molecule Libraries, Support Vector Machine

Quantitative microscopy has proven a versatile and powerful phenotypic screening technique. Recently, image-based profiling has shown promise as a means for broadly characterizing molecules' effects on cells in several drug-discovery applications, including target-agnostic screening and predicting a compound's mechanism of action (MOA). Several profiling methods have been proposed, but little is known about their comparative performance, impeding the wider adoption and further development of image-based profiling. We compared these methods by applying them to a widely applicable assay of cultured cells and measuring the ability of each method to predict the MOA of a compendium of drugs. A very simple method that is based on population means performed as well as methods designed to take advantage of the measurements of individual cells. This is surprising because many treatments induced a heterogeneous phenotypic response across the cell population in each sample. Another simple method, which performs factor analysis on the cellular measurements before averaging them, provided substantial improvement and was able to predict MOA correctly for 94% of the treatments in our ground-truth set. To facilitate the ready application and future development of image-based phenotypic profiling methods, we provide our complete ground-truth and test data sets, as well as open-source implementations of the various methods in a common software framework.


Alternate JournalJ Biomol Screen
PubMed ID24045582
PubMed Central IDPMC3884769
Grant ListU54 HG005032 / HG / NHGRI NIH HHS / United States
U54-HG005032 / HG / NHGRI NIH HHS / United States