README.md

The scripts in this repo can be used to run the analyses conducted in the Stagaman et al. 2024 article, {TITLE} published in Communications Medicine.

File descriptions:

1. .Rprofile creates a list of directories for reading in and saving data and plots
2. _packages_and_sources.R
3. _setup.R loads packages, sources functions, set important variables
4. 01_variable_reduction_selection.R Conducts the variable reduction step to identify the covariates to be used in all subsequent analyses.
5. 02_Analyses all scripts used for statistical analyses
   1. 01_required_first.R removes low abundance and low prevalence OTUs/KOs, rarefies counts, and generates data structures to be used in differential abundances and random forest analyses
   2. 02_taxonomic_alpha.R conducts statistical analysis of alpha-diversity in relation to PD and the covariates of interest.
   3. 03_all_beta.R conducts statistical analysis of beta-diversity in relation to PD and the covariates of interest.
   4. 04_random_forests scripts used for random forest classfier models
      1. 04A_covariates_split_sources.R RF model training and testing for saliva and stool separately using only covariate data (no OTU or KO abundances).
      2. 04B_covariates_combined_sources.R RF model training and testing for saliva and stool combined using only covariate data (no OTU or KO abundances).
      3. 04C_taxon_abunds_split_types_split_sources.R RF model training and testing for saliva and stool separately using OTU, species, and genus abundances separately.
      4. 04D_taxon_abunds_split_types_combined_sources.R RF model training and testing for saliva and stool combined using OTU, species, and genus abundances separately.
      5. 04E_taxon_abunds_aggregated_split_sources.R RF model training and testing for saliva and stool separately using OTU, species, and genus abundances combined.
      6. 04F_taxon_abunds_aggregated_combined_sources.R RF model training and testing for saliva and stool combined using OTU, species, and genus abundances combined.
      7. 04G_taxon_abunds_covariates_split_types_split_sources.R RF model training and testing for saliva and stool separately using OTU, species, and genus abundances separately, including covariates.
      8. 04H_taxon_abunds_covariates_split_types_combined_sources.R RF model training and testing for saliva and stool combined using OTU, species, and genus abundances separately, including covariates.
      9. 04I_taxon_abunds_covariates_aggregated_split_sources.R RF model training and testing for saliva and stool separately using OTU, species, and genus abundances combined, including covariates.
      10. 04J_taxon_abunds_covariates_aggregated_combined_sources.R RF model training and testing for saliva and stool combined using OTU, species, and genus abundances combined, including covariates.
      11. 04K_function_abunds_split_types_split_sources.R RF model training and testing for saliva and stool separately using KO, module, and pathway abundances separately
      12. 04L_function_abunds_covars_split_types_split_sources.R RF model training and testing for saliva and stool separately using KO, module, and pathway abundances separately, including covariates.
   5. 05_LDAs scripts used for differential abundance analsyes (a.k.a linear discriminate analyses)
      1. 05A_taxon_ANCOMBC2_wCovariates.R Differential OTU abundance analysis using ANCOMBC2, including covariates.
      2. 05B_taxon_ANCOMBC2_PDonly.R Differential OTU abundance analysis using ANCOMBC2, without covariates.
      3. 05C_taxon_ALDEx2_wCovariates.R Differential OTU abundance analysis using ALDEx2, including covariates.
      4. 05D_taxon_ALDEx2_PDonly.R Differential OTU abundance analysis using ALDEx2, without covariates.
      5. 05E_function_ANCOMBC2_wCovariates.R Differential KO abundance analysis using ANCOMBC2, including covariates.
      6. 05F_function_ANCOMBC2_PDonly.R Differential KO abundance analysis using ANCOMBC2, without covariates.
      7. 05G_function_ALDEx2_wCovariates.R Differential KO abundance analysis using ALDEx2, including covariates.
      8. 05H_function_ALDEx2_PDonly.R Differential KO abundance analysis using ALDEx2, without covariates.
   6. 06_networks scripts used to generate feature-feature (OTUs/KOs) networks
      1. 06A_between_saliva_stool_associations.R Generates OTU-OTU and KO-KO co-abundance networks (utilizing SpeicEasi) between saliva and stool microbiomes.
      2. 06B_within_sample_associations.R Generates OTU-OTU and KO-KO co-abundance networks (utilizing SpeicEasi) within saliva and stool microbiomes.
   7. 99_required_last.R merges data from across different scripts in prepartion for plotting and further analysis.
6. Helpers scripts for custom functions and model specifications used across scripts
   1. functions.R custom functions
   2. model_specs.R model specifications