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Article
Nature Methods - 4, 445 - 453 (2007)
Published online: 1 April 2007; | doi:10.1038/nmeth1032

Image-based multivariate profiling of drug responses from single cells

Lit-Hsin Loo, Lani F Wu & Steven J Altschuler

Department of Pharmacology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., ND 9.214, Dallas, Texas 75390, USA.

Correspondence should be addressed to Steven J Altschuler steven.altschuler@utsouthwestern.edu

Quantitative analytical approaches for discovering new compound mechanisms are required for summarizing high-throughput, image-based drug screening data. Here we present a multivariate method for classifying untreated and treated human cancer cells based on approx300 single-cell phenotypic measurements. This classification provides a score, measuring the magnitude of the drug effect, and a vector, indicating the simultaneous phenotypic changes induced by the drug. These two quantities were used to characterize compound activities and identify dose-dependent multiphasic responses. A systematic survey of profiles extracted from a 100-compound compendium of image data revealed that only 10–15% of the original features were required to detect a compound effect. We report the most informative image features for each compound and fluorescence marker set using a method that will be useful for determining minimal collections of readouts for drug screens. Our approach provides human-interpretable profiles and automatic determination of on- and off-target effects.

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Nature Methods
ISSN: 1548-7091
EISSN: 1548-7105
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