Reproducible analysis for Sanchez-Contreras M and Sweetwyne MT, et al., Elife, 12:e83395, 2023. https://doi.org/10.7554/eLife.83395

Repository contains the necessary data and python scripts to generate nearly all of the figures and reported p-values. Reproducibility is done using Snakemake

Requirements

Snakemake Anaconda/miniconda

Data Extraction

• 'compile_data.py': Reads the individual data and/or summary files and compiles them into .csv files used for plotting (stored in the 'data/imported_data' subdirectory).

Statistical Analysis

• 'compute_stats.py': Computes p-values used to establish significance and then reports them as .csv files for each figure or subfigure. Specific figure is indicated in the file name (stored in the data/stats/ subdirectory)
• 'fold_change.R': Computes the fold change and p-values using the mratios R package used in Figure 3.
• 'Dunnett_test.R': Computes the adjusted p-value using the DescTools R package and used in Figure 6.

Figure Scripts

The scripts generate each of the figures in the paper. They are contained in .py files with names corresponding to the relevant figure.

Miscellaneous

• 'GlobalVars_.py': Contains global variables used across multiple figure generation and analysis scripts.
• 'HelperFuncs_.py': Functions used for formatting data
• 'run.py': A standalone script that will generate the figures and statistical files without Snakemake or conda.

Howto

• Install Conda or Miniconda
• Install Snakemake and Mamba (conda install snakemake mamba)
• Clone the repository
• Setup the environment (snakemake --cores 1 --use-conda --conda-frontend mamba --conda-prefix .snakemake -- initializeEnvs)
• Perform reproducibile analysis (snakemake -s snakefile --use-conda --keep-going -j 1 --conda-prefix .snakemake)