Abstract
Sylamer is a method for detecting microRNA target and small interfering RNA off-target signals in 3′ untranslated regions from a ranked gene list, sorted from upregulated to downregulated, after a microRNA perturbation or RNA interference experiment. The output is a landscape plot that tracks occurrence biases using hypergeometric P-values for all words across the gene ranking. We demonstrated the utility, speed and accuracy of this approach on several datasets.
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Acknowledgements
We thank R. Grocock, W. Khong, H. Saini, S. Manakov, J. van Helden, A. Giraldez and W. Huber for useful discussions. This work was supported by the Wellcome Trust.
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Authors and Affiliations
Contributions
S.v.D., C.A.-G. and A.J.E. conceived and designed the method. S.v.D. implemented the method. C.A.-G. and S.v.D. perfomed the analyses and validation experiments. S.v.D., C.A.-G. and A.J.E. wrote the manuscript.
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Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–6, Supplementary Discussion, Supplementary Methods (PDF 7562 kb)
Supplementary Data 1
miR-155 genelists and sequences (ZIP 6555 kb)
Supplementary Data 2
miR-430 genelists and sequences (ZIP 1884 kb)
Supplementary Data 3
siRNA genelists and sequences (ZIP 8595 kb)
Supplementary Software
Sylamer source-code, binaries and JAVA interface (ZIP 9834 kb)
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van Dongen, S., Abreu-Goodger, C. & Enright, A. Detecting microRNA binding and siRNA off-target effects from expression data. Nat Methods 5, 1023–1025 (2008). https://doi.org/10.1038/nmeth.1267
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DOI: https://doi.org/10.1038/nmeth.1267
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