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With the development of next generation high-throughput sequencing solutions to expression profiling, the efficient and effortless handling of such profiling data became a key challenge for bioinformaticians and biologists alike. We therefore present a "fire and forget" style pipeline implemented in C and R, named QUASI. It is capable of quality assessments, sequence alignments, shRNA quantification and statistically inferring significant differential sequence abundance from datasets presented to it. Through blackboxing the often complex and laborious steps, QUASI presents itself as a user-friendly and time-efficient solution to handle pooled shRNA library screening data.

QUASI: A Pipeline for the Quality Assessment and Statistical Inference on Next Generation Sequencing Data from Pooled shRNA Library Screens