TY - JOUR
T1 - IScreen
T2 - Image-Based High-Content RNAi Screening Analysis Tools
AU - Zhong, Rui
AU - Dong, Xiaonan
AU - Levine, Beth
AU - Xie, Yang
AU - Xiao, Guanghua
N1 - Funding Information:
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by National Institutes of Health grants 5R01CA152301, 1R01CA172211, and U19AI109725 and by Cancer Prevention Research Institute of Texas awards RP101251 and RP120718.
Publisher Copyright:
© 2015 Society for Laboratory Automation and Screening.
PY - 2015/9/24
Y1 - 2015/9/24
N2 - 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.
AB - 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.
KW - RNA interference
KW - RNAi
KW - genomics
KW - high-content screening
KW - shRNA
KW - statistical analyses
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U2 - 10.1177/1087057114564348
DO - 10.1177/1087057114564348
M3 - Article
C2 - 25548139
AN - SCOPUS:84939808863
SN - 1087-0571
VL - 20
SP - 998
EP - 1002
JO - Journal of Biomolecular Screening
JF - Journal of Biomolecular Screening
IS - 8
ER -