@inbook{8b8d009330a44745b6e4b45da0de54e0,
title = "Pooled ShRNA screenings: Computational analysis",
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.",
keywords = "Barcode, Decoding, Differential representation, GSEA, Genome-wide, Microarray, Next-generation sequencing, Normalization, Pooled shRNA screen, QA",
author = "Jiyang Yu and Preeti Putcha and Andrea Califano and Silva, {Jose M.}",
year = "2013",
doi = "10.1007/978-1-62703-287-2_22",
language = "English",
isbn = "9781627032865",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "371--384",
booktitle = "Pancreatic Cancer",
}