Cell-Based Assays for High-Throughput Screening pp 193-211

Part of the Methods in Molecular Biology book series (MIMB, volume 486)

Extracting Rich Information from Images

Protocol

Summary

Now that automated image-acquisition instruments (high-throughput microscopes) are commercially available and becoming more widespread, hundreds of thousands of cellular images are routinely generated in a matter of days. Each cellular image generated in a high-throughput screening experiment contains a tremendous amount of information; in fact, the name high-content screening (HCS) refers to the high information content inherently present in cell images (J Biomol Screen 2:249–259, 1997). Historically, most of this information is ignored and the visual information present in images for a particular sample is often reduced to a single numerical output per well, usually by calculating the mean per-cell measurement for a particular feature. Here, we provide a detailed protocol for the use of open-source cell image analysis software, CellProfiler, to measure hundreds of features of each individual cell, including the size and shape of each compartment or organelle, and the intensity and texture of each type of staining in each subcompartment. We use as an example publicly available images from a cytoplasm-to-nucleus translocation assay.

Key words

Complex phenotypes Data visualization High-content screening High-throughput data analysis Microscopy Visual phenotypes 

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Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Imaging Platform, Broad Institute of Harvard and MITCambridgeUSA

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