Analysis of image-based phenotypic parameters for high throughput gene perturbation assays

Mee Song, Euna Jeong, Tae Kyu Lee, Yury Tsoy, Yong Jun Kwon, Sukjoon Yoon*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

5 Citations (Scopus)


Although image-based phenotypic assays are considered a powerful tool for siRNA library screening, the reproducibility and biological implications of various image-based assays are not well-characterized in a systematic manner. Here, we compared the resolution of high throughput assays of image-based cell count and typical cell viability measures for cancer samples. It was found that the optimal plating density of cells was important to obtain maximal resolution in both types of assays. In general, cell counting provided better resolution than the cell viability measure in diverse batches of siRNAs. In addition to cell count, diverse image-based measures were simultaneously collected from a single screening and showed good reproducibility in repetitions. They were classified into a few functional categories according to biological process, based on the differential patterns of hit (i.e., siRNAs) prioritization from the same screening data. The presented systematic analyses of image-based parameters provide new insight to a multitude of applications and better biological interpretation of high content cell-based assays.

Original languageEnglish
Pages (from-to)192-198
Number of pages7
JournalComputational Biology and Chemistry
Publication statusPublished - 11 Aug 2015
Externally publishedYes


  • Gene perturbation
  • Image-based assay
  • Phenotypic parameter
  • siRNA screening

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