Abstract

BackgroundRNAi 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.ResultsHere, 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.ConclusionsOur software package, ScreenSifter, can accelerate and facilitate screen data analysis and enable discovery by providing unique biological data visualization capabilities.

Highlights

  • RNA interference (RNAi) screening is a powerful method to study the genetics of intracellular processes in metazoans

  • RNAi is a conserved biological phenomenon through which gene expression can be silenced by the endogenous cellular machinery at the level of individual transcripts, with specificity conferred by the sequence of double-stranded RNA or small-interfering RNA [3]

  • A primary data file is uploaded for each Screen and forms a primary Data Table; subsequently derived Data Tables can be saved under the same Screen

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Summary

Results

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 metadata 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 allows the visualization of screen-to-screen comparisons

Background
B Score is calculated for each record using the following formula
Results and discussion
Conclusions
12. Cullen BR
Full Text
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