POWSC

"POWSC" (Power Evaluation and Sample Size Calculation for Single-Cell RNA-Sequencing Differential Expression Analysis) is a simulation-based method to address the critical need for power evaluation and sample size recommendations in single-cell RNA sequencing (scRNA-seq) experiments. Given the unique challenges presented by the sparsity and heterogeneity of scRNA-seq data, POWSC offers a novel approach to ensure that high-throughput experiments are adequately powered to detect statistical significance in differential expression (DE) analysis.

Key Features and Functionalities:

Realistic Data Simulation: POWSC includes a data simulator that generates realistic expression data, more accurately capturing the key characteristics of real scRNA-seq datasets than other state-of-the-art simulators.

- Comprehensive Power Evaluation: The power assessor component of POWSC provides a detailed evaluation of the power and sample size relationship, including stratified and marginal power analyses for DEs characterized by phase transition or magnitude tuning across various comparison scenarios.

- Optimization of Sample Size and Sequencing Depth: POWSC uniquely offers insights into optimizing the trade-offs between sample size and sequencing depth, enabling researchers to make informed decisions on resource allocation without compromising the total number of reads.

- Visualization Tools: The package includes visualization tools for the comprehensive evaluation of power and sample size, aiding in interpreting and planning scRNA-seq experiments.