High-Dimensional Profiling: The Theta Comparative Cell Scoring Method

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract / Description of output

Principal component analysis enables dimensional reduction of multivariate datasets that are typical in high-content screening. A common analysis utilizing principal components is a distance measurement between a perturbagen—such as small-molecule treatment or shRNA knockdown—and a negative control. This method works well to identify active perturbagens, though it cannot discern between distinct phenotypic responses. Here, we describe an extension of the principal component analysis approach to multivariate high-content screening data to enable quantification of differences in direction in principal component space. The theta comparative cell scoring method can identify and quantify differential phenotypic responses between panels of cell lines to small-molecule treatment to support in vitro pharmacogenomics and drug mechanism-of-action studies
Original languageEnglish
Title of host publicationPhenotypic Screening
Subtitle of host publicationMethods in Molecular Biology
Publication statusPublished - 8 May 2018

Publication series

NameMethods in Molecular Biology
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords / Materials (for Non-textual outputs)

  • Cell-based profiling
  • High-content analysis
  • Phenotypic screening


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