The Power Decoder Simulator for the Evaluation of Pooled shRNA Screen Performance.

Area of Science:

• Genomics and Bioinformatics
• Molecular Biology
• Computational Biology

Background:

• RNA interference (RNAi) screening with pooled short hairpin RNA (shRNA) is a high-throughput method for identifying genes critical to phenotypes.
• Evaluating the performance and statistical power of shRNA pooled screens is challenging, often relying on reproducibility or numerous controls.

Purpose of the Study:

• To develop an open-source software tool, the Power Decoder simulator, for estimating the statistical power of shRNA pooled screening experiments.
• To provide a computational method for assessing screen performance without requiring additional experimental data.

Main Methods:

• Developed the Power Decoder simulator using R and Python.
• Employed the negative binomial distribution to model shRNA relative abundance within replicates and biological noise between replicates.
• Validated the simulator by demonstrating its ability to model data from a real laboratory experiment.

Main Results:

• The Power Decoder simulator accurately models shRNA pooled screening data.
• The tool enables evaluation of factors like biological replicates and sequencing depth on screen performance.
• Demonstrated the simulator's utility in assessing screen power in silico.

Conclusions:

• The Power Decoder simulator is a valuable tool for estimating statistical power in shRNA pooled screens.
• This software facilitates improved experimental design and performance assessment for RNAi screening studies.
• The open-source nature of the simulator promotes accessibility and further development in the field.