VGO3 upper airway microbiome in pneumonia analysis code

This code accompanies the manuscript 'Upper airway microbiota in individuals with community-acquired pneumonia: A case-control study in rural general practice patients'. How to cite this material: 10.5281/zenodo.15915888 Description This repository contains the Rmd-scripts used to generate results. The code below was ran in R (v4.4.3). Scripts for data analysis 0.1_descriptive_statistics.Rmd : Generating baseline tables of the phenotypic data from the participants and study collinearity between the variables. 0.2_univariable_permanova.Rmd : Univariable PERMANOVA analyses. Stratified by pneumonia status. 1.1_beta_alpha_diversity.Rmd : Beta-diversity analyses (PERMANOVA) and microbial diversity and density across pneumonia status. 1.2_cluster_analysis.Rmd : Clustering individuals based on similar microbial profiles and performing cluster analysis by pneumonia status. 1.3_differential_abundance_ASV.Rmd : Differential abundance analyses MaAsLin2 and ANCOM-BC2 on ASV-level. 1.3_differential_abundance_Genus.Rmd : Differential abundance analyses MaAsLin2 and ANCOM-BC2 on genus-level. 1.4_network_analysis.Rmd : Network analyses including nasopharyngeal and oropharyngeal ASVs, stratified by pneumonia status. 1.5_machine_learning.Rmd : Machine learning to predict the most important microbial features for discriminating pneumonia cases from controls. 1.6_presence_absence.Rmd : Presence-absence based analyses using Fisher's exact tests. 1.7_functional_abundance.Rmd : Differential abundance analyses MaAsLin2 and ANCOM-BC2, focused on functional pathways predicted by PICRUSt2. 2.1_beta_alpha_diversity.Rmd : Beta-diversity analyses (PERMANOVA) and microbial diversity and density across comorbidities, medication use and symptoms within pneumonia cases. 2.2_differential_abundance.Rmd : Differential abundance analyses MaAsLin2 and ANCOM-BC2 on ASV-level across comorbidities, medication use and symptoms within pneumonia cases. Other analyses SRA_upload.Rmd : Script used to prepare data for SRA-upload. The .html-output of all the scripts can be found the `results`-folder.