IScreen: Image-Based High-Content RNAi Screening Analysis Tools

Rui Zhong, Xiaonan Dong, Beth Levine, Yang Xie, Guanghua Xiao

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

High-throughput RNA interference (RNAi) screening has opened up a path to investigating functional genomics in a genome-wide pattern. However, such studies are often restricted to assays that have a single readout format. Recently, advanced image technologies have been coupled with high-throughput RNAi screening to develop high-content screening, in which one or more cell image(s), instead of a single readout, were generated from each well. This image-based high-content screening technology has led to genome-wide functional annotation in a wider spectrum of biological research studies, as well as in drug and target discovery, so that complex cellular phenotypes can be measured in a multiparametric format. Despite these advances, data analysis and visualization tools are still largely lacking for these types of experiments. Therefore, we developed iScreen (image-Based High-content RNAi Screening Analysis Tool), an R package for the statistical modeling and visualization of image-based high-content RNAi screening. Two case studies were used to demonstrate the capability and efficiency of the iScreen package. iScreen is available for download on CRAN (http://cran.cnr.Berkeley.edu/web/packages/iScreen/index.html). The user manual is also available as a supplementary document.

Original languageEnglish (US)
Pages (from-to)998-1002
Number of pages5
JournalJournal of Biomolecular Screening
Volume20
Issue number8
DOIs
StatePublished - Sep 24 2015

Keywords

  • RNA interference
  • RNAi
  • genomics
  • high-content screening
  • shRNA
  • statistical analyses

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biotechnology
  • Biochemistry
  • Molecular Medicine
  • Pharmacology
  • Drug Discovery

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