MAUDE-Py: A Python Implementation for Analyzing Sorting-Based Pooled CRISPR Screens

The Python programming language is gaining popularity in bioinformatics owing to its versatility in computing-heavy applications. An area of particular interest where computational power can be leveraged is analyzing and interpreting pooled CRISPR screens. Here, we replicate the core functionality of an existing platform, Mean Alterations Using Discrete Expression (MAUDE), in Python (MAUDE-Py) to analyze pooled CRISPR screens. Our tool complements the original R MAUDE software as a robust and user-friendly Python package that integrates with existing CRISPR analysis workflows. While preserving the core probabilistic framework of MAUDE, MAUDE-Py introduces notable enhancements. These enhancements include automated baseline calculations, a more robust null-sampling methodology for determining significance at both the gene and non-coding element levels, and an integrated visualization suite for displaying the analyzed results. Benchmarking MAUDE-Py against the original MAUDE on a series of datasets demonstrates a 2.09x to 4.19x speedup in execution time while achieving near-perfect consistency, confirming that our Python implementation is a highly accurate and viable alternative for such analyses.