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

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

Research output: Contribution to journalArticle

2 Citations (Scopus)

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

Fingerprint

RNA Interference
Screening
RNA
Genome
Technology
Drug Discovery
Genomics
Genes
Throughput
Data visualization
Phenotype
Assays
Visualization
Research
Pharmaceutical Preparations
Experiments

Keywords

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

ASJC Scopus subject areas

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

Cite this

IScreen : Image-Based High-Content RNAi Screening Analysis Tools. / Zhong, Rui; Dong, Xiaonan; Levine, Beth; Xie, Yang; Xiao, Guanghua.

In: Journal of Biomolecular Screening, Vol. 20, No. 8, 24.09.2015, p. 998-1002.

Research output: Contribution to journalArticle

@article{6fd7b0a444fb4f92949ffb6fe1c4891e,
title = "IScreen: Image-Based High-Content RNAi Screening Analysis Tools",
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.",
keywords = "genomics, high-content screening, RNA interference, RNAi, shRNA, statistical analyses",
author = "Rui Zhong and Xiaonan Dong and Beth Levine and Yang Xie and Guanghua Xiao",
year = "2015",
month = "9",
day = "24",
doi = "10.1177/1087057114564348",
language = "English (US)",
volume = "20",
pages = "998--1002",
journal = "Journal of Biomolecular Screening",
issn = "1087-0571",
publisher = "SAGE Publications Inc.",
number = "8",

}

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

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 - genomics

KW - high-content screening

KW - RNA interference

KW - RNAi

KW - shRNA

KW - statistical analyses

UR - http://www.scopus.com/inward/record.url?scp=84939808863&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84939808863&partnerID=8YFLogxK

U2 - 10.1177/1087057114564348

DO - 10.1177/1087057114564348

M3 - Article

C2 - 25548139

AN - SCOPUS:84939808863

VL - 20

SP - 998

EP - 1002

JO - Journal of Biomolecular Screening

JF - Journal of Biomolecular Screening

SN - 1087-0571

IS - 8

ER -