IScreen: Image-Based High-Content RNAi Screening Analysis Tools. (September 2015)

• Record Type: Journal Article
• Authors: Zhong, Rui; Dong, Xiaonan; Levine, Beth; Xie, Yang; Xiao, Guanghua
• Other Names: Bickle Marc guest-editor.; Djaballah Hakim guest-editor.; Mayr Lorenz Martin guest-editor.
• Is Part Of: Journal of biomolecular screening. Volume 20:Number 8(2015)
• Page Start: 998
• Page End: 1002
• Publication Date: 2015-09
• Subjects: high-content screening -- statistical analyses -- RNA interference -- RNAi -- shRNA -- genomics; Drugs -- Analysis -- Periodicals; Drugs -- Testing -- Periodicals; Biomolecules -- Analysis -- Periodicals; 572.36
• DOI: 10.1177/1087057114564348
• Languages: English
• ISSNs: 1087-0571

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.