Abstract
Genome-wide RNA interference screening has emerged as a powerful tool for functional genomic studies of disease-related phenotypes and the discovery of molecular therapeutic targets for human diseases. Commercial short hairpin RNA (shRNA) libraries are commonly used in this area, and state-of-the-art technologies including microarray and next-generation sequencing have emerged as powerful methods to analyze shRNA-triggered phenotypes. However, computational analysis of this complex data remains challenging due to noise and small sample size from such large-scaled experiments. In this chapter we discuss the pipelines and statistical methods of processing, quality assessment, and post-analysis for both microarray- and sequencing-based screening data.
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Yu, J., Putcha, P., Califano, A., Silva, J.M. (2013). Pooled ShRNA Screenings: Computational Analysis. In: Su, G. (eds) Pancreatic Cancer. Methods in Molecular Biology, vol 980. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-287-2_22
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DOI: https://doi.org/10.1007/978-1-62703-287-2_22
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