dms_tools2

dms_tools2 infers site-specific amino-acid preferences and mutational effects from deep mutational scanning (DMS) data generated by comprehensive codon mutagenesis of protein-coding genes, using deep sequencing of variant libraries before and after functional selection.

Key Features:

• Likelihood-Based Inference: Employs a likelihood-based statistical framework to interpret mutation counts and infer mutational effects from sequencing data.
• Site-Specific Amino Acid Preferences: Estimates amino-acid preferences at individual protein sites and quantifies shifts in these preferences under different selection pressures.
• Visualization Tools: Produces sequence-logo-style plots via weblogo to visualize amino-acid preferences and their changes across conditions.

Scientific Applications:

• Evolutionary Biology: Quantifies how protein amino-acid preferences change under environmental or functional pressures to elucidate adaptation.
• Functional Genomics: Maps residues critical for gene function by measuring effects of codon mutations on selection outcomes.
• Drug Discovery: Identifies mutations and sites that alter protein function to inform therapeutic target characterization.

Methodology:

Performs a statistically principled analysis by comparing pre-selection and post-selection mutation counts using a likelihood-based inference approach.