rSalvador

rSalvador computes mutation rates from Luria-Delbrück fluctuation assay data and provides analysis that corrects for partial plating, integrates mutants' relative fitness, estimates required sample sizes, and addresses parameter nonidentifiability for bacterial mutation studies.

Key Features:

• Comprehensive data analysis: Accounts for partial plating effects when analyzing fluctuation assay results to improve accuracy of mutation rate estimates.
• Incorporation of mutants' relative fitness: Integrates mutants' relative fitness into mutation rate calculations to reflect fitness-dependent effects.
• Mutation rate comparison methods: Implements methods specifically applicable to fluctuation assay data for valid comparisons of mutation rates.
• Sample size estimation: Estimates the necessary sample size for fluctuation assay experiments to support experimental design and power considerations.
• Addressing parameter nonidentifiability: Provides strategies to manage parameter nonidentifiability inherent in fluctuation assay analyses.

Scientific Applications:

• Bacterial mutation rate estimation: Estimating mutation rates from Luria-Delbrück fluctuation assay data.
• Mutational dynamics analysis: Investigating mutational dynamics in bacterial populations analyzed by fluctuation assays.
• Assessing fitness landscapes: Assessing mutants' relative fitness and its impact on observed mutation frequencies.
• Experimental design for fluctuation assays: Informing sample-size planning and study design for fluctuation assay experiments.

Methodology:

Implements analysis routines that correct for partial plating, integrate mutants' relative fitness into mutation rate estimation, apply fluctuation-assay-specific methods for mutation-rate comparisons, estimate required sample sizes, and apply strategies to address parameter nonidentifiability.