An interactive web-based application for Comprehensive Analysis of RNAi-screen Data

Bhaskar Dutta (), Alaleh Azhir, Louis-Henri Merino, Yongjian Guo, Swetha Revanur, Piyush B. Madhamshettiwar, Ronald N. Germain, Jennifer A. Smith, Kaylene J. Simpson, Scott E. Martin, Eugen Buehler and Iain D. C. Fraser ()
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Bhaskar Dutta: Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health
Alaleh Azhir: Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health
Louis-Henri Merino: Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health
Yongjian Guo: Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health
Swetha Revanur: Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health
Piyush B. Madhamshettiwar: Victorian Centre for Functional Genomics, Peter MacCallum Cancer Centre
Ronald N. Germain: Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health
Jennifer A. Smith: ICCB-Longwood Screening Facility, Harvard Medical School
Kaylene J. Simpson: Victorian Centre for Functional Genomics, Peter MacCallum Cancer Centre
Scott E. Martin: National Center for Advancing Translational Sciences, National Institutes of Health
Eugen Buehler: National Center for Advancing Translational Sciences, National Institutes of Health
Iain D. C. Fraser: Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health

Nature Communications, 2016, vol. 7, issue 1, 1-15

Abstract: Abstract RNAi screens are widely used in functional genomics. Although the screen data can be susceptible to a number of experimental biases, many of these can be corrected by computational analysis. For this purpose, here we have developed a web-based platform for integrated analysis and visualization of RNAi screen data named CARD (for Comprehensive Analysis of RNAi Data; available at https://card.niaid.nih.gov ). CARD allows the user to seamlessly carry out sequential steps in a rigorous data analysis workflow, including normalization, off-target analysis, integration of gene expression data, optimal thresholds for hit selection and network/pathway analysis. To evaluate the utility of CARD, we describe analysis of three genome-scale siRNA screens and demonstrate: (i) a significant increase both in selection of subsequently validated hits and in rejection of false positives, (ii) an increased overlap of hits from independent screens of the same biology and (iii) insight to microRNA (miRNA) activity based on siRNA seed enrichment.

Date: 2016
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DOI: 10.1038/ncomms10578

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