A challenge for large-scale siRNA loss-of-function studies is the biological pleiotropy resulting from multiple modes of action of siRNA reagents. A major confounding feature of these reagents is the microRNA-like translational quelling resulting from short regions of oligonucleotide complementarity to many different messenger RNAs. We developed a computational approach, deconvolution analysis of RNAi screening data, for automated quantitation of off-target effects in RNAi screening data sets. Substantial reduction of off-target rates was experimentally validated in five distinct biological screens across different genome-wide siRNA libraries. A public-access graphical-user-interface has been constructed to facilitate application of this algorithm. © 2014 The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
CITATION STYLE
Zhong, R., Kim, J., Kim, H. S., Kim, M., Lum, L., Levine, B., … Xie, Y. (2014). Computational detection and suppression of sequence-specific off-target phenotypes from whole genome RNAi screens. Nucleic Acids Research, 42(13), 8214–8222. https://doi.org/10.1093/nar/gku306
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