emmaewade / Lethals_Project

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Introduction to Lethals Project

This document was created as a repository of the scripts used in the analyses of the article: Wade, Kyriazis, Cavassim, Lohmueller. 2023. "Quantifying the fraction of new mutations that are recessive lethal." Evolution. (doi: XXXXX).

Files used in the pipeline are described as follow

  • sim.slim Forward in time simulations were conducted using the software SLiM 31.
  • demographic_inference.py This python script contains the code used for the inference demographic parameters using the software dadi2.
  • selection_inference.py This python script contains the code used for the inference of the distribution of fitness effects (DFE) using the software fitdadi3.

Script for Table 1's complex model analysis:

  • parse_inference_results_Table1.R

Table 1 Output:

  • inference_results.table.aug.2022.llike_cutoff_20.txt
  • inference_results.table.aug.2022.llike_cutoff_5.txt

Scripts for each figure are available in figures/scripts

Data produced to generate figures are:

  • figures/data/all_inferences.csv
  • figures/data/all_log_20_inferences.csv
  • figures/data/exp_v_inferred.csv
  • figures/data/sim_avg_sfs10.csv
  • figures/data/sim_avg_sfs100.csv
  • figures/data/sim_avg_sfs1000.csv
  • figures/data/computed_avg_sfs10.csv
  • figures/data/computed_avg_sfs100.csv
  • figures/data/computed_avg_sfs1000.csv

Scripts for mutation-selection-drift balance results are available at: https://github.com/ckyriazis/lethals_scripts

References

  • 1 Haller, Benjamin C., and Philipp W. Messer. 2019. “SLiM 3: Forward Genetic Simulations Beyond the Wright–Fisher Model.” Molecular Biology and Evolution 36 (3): 632–37.
  • 2 Gutenkunst, Ryan, Ryan Hernandez, Scott Williamson, and Carlos Bustamante. 2010. “Diffusion Approximations for Demographic Inference: DaDi.” Nature Precedings, June, 1–1.
  • 3 Kim, Bernard Y., Christian D. Huber, and Kirk E. Lohmueller. 2017. “Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples.” Genetics 206 (1): 345–61.

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Language:R 57.6%Language:Python 34.1%Language:Slim 8.4%