MAUDE

MAUDE quantifies changes in reporter gene expression induced by guide RNAs in sorting-based CRISPR screens using statistical modeling implemented as an R package.

Key Features:

• Quantification of guide RNA effects: Measures the impact of individual guide RNAs on target gene and reporter expression by analyzing cell distributions across discrete expression bins.
• Statistical modeling of bin distributions: Models the distribution of cell abundances across expression bins to estimate effect sizes and statistical significance of perturbations.
• Implementation: Provided as an R package for computational analysis of pooled sorting-based CRISPR screen data.
• Benchmarking: Experimental validations reported that MAUDE outperforms existing approaches in analyzing sorting-based CRISPR screen data.
• Experimental design guidelines: Supplies recommendations to optimize experimental design for sorting-based CRISPR screens.

Scientific Applications:

• Pooled sorting-based CRISPR screens: Quantitative analysis of guide RNA-induced expression changes in pooled, bin-sorted CRISPR experiments.
• Reporter gene assays: Assessment of perturbation effects on reporter gene expression across discrete expression bins.
• Functional genomics of genes and regulatory elements: Investigations to elucidate roles of genes and regulatory elements by quantifying expression alterations caused by targeted perturbations.

Methodology:

Models cell abundances across discrete expression bins assuming approximately normally distributed (or near-normal) data to quantify guide RNA-induced expression changes.