Nepali oral microbiomes reflect a gradient of lifestyles from traditional to industrialized

This repository contains all scripts used to generate the results for "Nepali oral microbiomes reflect a gradient of lifestyles from traditional to industrialized." All analyses start in the same base directory. All analyses are conducted in R, unless otherwise specified.

Note: all scripts assume that the working directory is set to a directory called Nepal_oral_microbiome\. Within Nepal_oral_microbiome\, there are sub-directories called data\, output\, and figures\. Within data\, there are directories called fwd\ and filt_path\. Data is stored in the fwd\ directory, while filt_path\ is empty. Note that, with the exception of the metadata table oralmicrobiome_surveydata.csv, data files are not included in the repo due to size but are included as supplemental tables in the publication or on SRA under BioProject PRJNA1098228.

Nepal_oral_microbiome
|- README		# Description of analysis scripts
|
|- data/		# Any data put into analyses - may be raw or processed (note: not version controlled currently due to size)
|    |- fwd/		          
|    |- filt_path/
|
|- output/		# Will contain output from scripts after they are run
|
|- figures/		# Will contain figures generated from scripts after they are run
+

All package info is in the R script package_info.R

Table of contents

1. oral_phyloseq.Rmd - clean 16S rRNA gene amplicon sequence data and generate phyloseq object
2. decontam.Rmd - remove potential contaminants
3. qc.Rmd - additional QC and cleaning of the phyloseq object
4. extraction_comparison.Rmd - compare Qiagen and PowerSoil extraction kit data
5. microbiome_characterization.Rmd - examine metrics for standard microbiome characteristics (alpha and beta diversity)
6. random_forest.Rmd - use Random Forests to predict lifestyle based on lifestyle survey and microbiome data
7. differential_abundance.Rmd - perform differential abundance analysis with ALDEx2 to identify taxa that differ based on lifestyle
8. microbiome_trend.Rmd - perform trend test on all genera to see which microbial abundances follow the lifestyle trend
9. CCA.Rmd - conduct CCA to identify which specific lifestyle factors correlate with microbiome composition
10. taxa_lifestyle.Rmd - identify significant associations between specific lifestyle factors and DA microbes identified from the trend test.
11. picrust2_prep.Rmd - prepping data for PICRUSt2
12. picrust_stratified.sh (shell) - run stratified version of PICRUSt2 to predict pathway abundances.
13. picrust_analysis.Rmd - analyze PICRUSt2 output. All PICRUSt2 output from picrust_stratified.sh is assumed to be stored in its own directory picrust2_qiagen_output\
14. network_analysis.Rmd - conduct network analysis of the microbiome using SparCC
15. gut_oral_comparison.Rmd - examine the relationship between the oral and gut microbiomes