Cell-Based Assays for High-Throughput Screening

Volume 486 of the series Methods in Molecular Biology pp 193-211


Extracting Rich Information from Images

  • Anne E. CarpenterAffiliated withImaging Platform, Broad Institute of Harvard and MIT Email author 

* Final gross prices may vary according to local VAT.

Get Access


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