mutscan

mutscan processes multiplexed assays of variant effect (MAVE) sequencing data to quantify variant abundances and identify effects of sequence variants through preprocessing, statistical modeling, and visualization.

Key Features:

• End-to-End Workflow: Processes raw sequencing reads through preprocessing, statistical analysis, and result visualization for MAVE datasets.
• C++ Implementation: Core components are implemented in C++ to improve computational efficiency on large datasets.
• Experimental Design Support: Handles single or paired reads and configurations that use unique molecular identifiers (UMIs).
• Statistical Modeling: Identifies variants with changes in relative abundance using models from the edgeR and limma packages.
• Visualization: Provides features for visualizing analysis results to aid interpretation of variant effects.

Scientific Applications:

• MAVE experiments: Quantitative analysis of multiplexed assays of variant effect to measure impacts of numerous sequence variants.
• Functional genomics: Interpreting variant effects in studies of gene and protein function.
• Personalized medicine: Supporting variant interpretation relevant to therapeutic strategies and genetic research.

Methodology:

Accepts raw sequencing reads from MAVE experiments; preprocesses data with C++-implemented components for efficiency; applies edgeR and limma statistical models to identify variants with significant changes in abundance; and generates visualizations of the results.