Please use this identifier to cite or link to this item: https://doi.org/10.1186/1471-2105-14-290
Title: ScreenSifter: Analysis and visualization of RNAi screening data
Authors: Kumar, P
Goh, G
Wongphayak, S
Moreau, D
Bard, F 
Keywords: Biological data mining
Biological data visualizations
Compound screenings
Desktop applications
Intracellular process
Protein-protein interactions
Software applications
Techniques and tools
Application programs
Data mining
Data reduction
Database systems
Digital storage
Genes
Graphical user interfaces
Proteins
Visualization
Data visualization
article
biology
computer interface
computer program
data mining
Internet
methodology
nucleic acid database
RNA interference
Computational Biology
Data Mining
Databases, Nucleic Acid
Internet
RNA Interference
Software
User-Computer Interface
Issue Date: 2013
Citation: Kumar, P, Goh, G, Wongphayak, S, Moreau, D, Bard, F (2013). ScreenSifter: Analysis and visualization of RNAi screening data. BMC Bioinformatics 14 (1) : 290. ScholarBank@NUS Repository. https://doi.org/10.1186/1471-2105-14-290
Rights: Attribution 4.0 International
Abstract: Background: RNAi screening is a powerful method to study the genetics of intracellular processes in metazoans. Technically, the approach has been largely inspired by techniques and tools developed for compound screening, including those for data analysis. However, by contrast with compounds, RNAi inducing agents can be linked to a large body of gene-centric, publically available data. However, the currently available software applications to analyze RNAi screen data usually lack the ability to visualize associated gene information in an interactive fashion.Results: Here, we present ScreenSifter, an open-source desktop application developed to facilitate storing, statistical analysis and rapid and intuitive biological data mining of RNAi screening datasets. The interface facilitates meta-data acquisition and long-term safe-storage, while the graphical user interface helps the definition of a hit list and the visualization of biological modules among the hits, through Gene Ontology and protein-protein interaction analyses. The application also allows the visualization of screen-to-screen comparisons.Conclusions: Our software package, ScreenSifter, can accelerate and facilitate screen data analysis and enable discovery by providing unique biological data visualization capabilities. © 2013 Kumar et al.; licensee BioMed Central Ltd.
Source Title: BMC Bioinformatics
URI: https://scholarbank.nus.edu.sg/handle/10635/181551
ISSN: 14712105
DOI: 10.1186/1471-2105-14-290
Rights: Attribution 4.0 International
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