Public Data Resource

Supplementary data for "Distributions of fitness effects for amino acid changes from high-throughout mutagenesis experiments" (McCandlish and Stoltzfus, 2018)

Contact: Arlin B. Stoltzfus..
Identifier: doi:10.18434/M31970
Version: 1.0...

Description

McCandlish and Stoltzfus gathered data from deep mutational scanning experiments on 12 proteins, comprising 56641 distinct amino acid replacement mutations. By converting fitnesses to within-study quantiles, they combined results from all studies to draw general conclusions about distributions of fitness effects for the 380 different types of possible amino acid changes in proteins. They found that most replacements are neither conservative nor radical, but barely different from the background distribution. The shapes of these distributions can be approximated by a maximum-entropy model with only 1 parameter. This data package makes it possible to reproduce the main calculations used by Stoltzfus and McCandlish. The data also may be useful to researchers carrying out meta-analyses of mutation-scanning experiments or DFE experiments.
Research Topics: Mathematics and Statistics:Numerical methods and software, Chemistry:Molecular characterization, Bioscience:Engineering/synthetic biology    
Subject Keywords: mutation, deep mutational scanning, fitness, protein    

Data Access

These data are public.
Files

Loading file list...

About This Dataset

Version: 1.0...
Cite this dataset
Arlin B. Stoltzfus (2018), Supplementary data for "Distributions of fitness effects for amino acid changes from high-throughout mutagenesis experiments" (McCandlish and Stoltzfus, 2018), National Institute of Standards and Technology, https://doi.org/10.18434/M31970 (Accessed 2024-04-21)
Repository Metadata
Machine-readable descriptions of this dataset are available in the following formats:
NERDm
Access Metrics
Metrics data is not available for all datasets, including this one. This may be because the data is served via servers external to this repository.