SbacHTS: spatial background noise correction for high-throughput RNAi screening

Identification of therapeutic small-molecule leads in cultured cells using multiplexed pathway reporter readouts

The rapid expansion of molecular screening libraries in size and complexity in the last decade has outpaced the discovery rate of cost-effective strategies to single out reagents with sought-after cellular activities. In addition to representing high-priority therapeutic targets, intensely studied cell signaling systems encapsulate robust reference points for mapping novel chemical activities given our deep understanding of the molecular mechanisms that support their activity. In this chapter, we describe strategies for using transcriptional reporters of several well-interrogated signal transduction pathways coupled with high-throughput biochemical assays to fingerprint novel compounds for drug target identification agendas.

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

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.