mlcoley/coley-2026-gut-microbiota-kenya

Continuous within-rural settlement intensity and household exposures are associated with gut microbiota composition in young children in western Kenya # Analysis code: Settlement intensity and child gut microbiota composition in rural Kenya **Coley et al. (2026)** — *BMC Microbiome* (under review) This repository contains the R analysis code for the manuscript examining associations between the within-rural settlement intensity gradient and gut microbiota alpha and beta diversity in 85 children aged 2–5 years from a rural Kenyan cohort. --- ## Repository structure ``` code/ R analysis scripts (run in the order listed below) data/ Place OSF data files here before running (see data/README.md) output/ Created automatically at run time; receives all CSV and figure outputs ``` --- ## Data All data files are archived on OSF: **osf.io Raw sequencing reads are deposited at NCBI SRA: BioProject accession PRJNA1207554 See `data/README.md` for a full description of each file and download instructions. --- ## How to reproduce ### 1. Requirements - R ≥ 4.2 - Key packages: `phyloseq`, `vegan`, `ALDEx2`, `maaslin3`, `zCompositions`, `picante`, `phytools`, `mediation`, `broom`, `car`, `tidyverse`, `ggrepel`, `cowplot`, `officer`, `flextable` Install from Bioconductor where needed: ```r BiocManager::install(c("phyloseq", "ALDEx2", "maaslin3")) ``` ### 2. Configure paths Open `code/sgma1_1_data-prep.R` and `code/sgma1_1_landscape.R` and set `proj_dir` to the root of this repository (the folder containing `code/` and `data/`). Also set `qiime_dir` and `seq_path` to wherever you have placed the QIIME2 output files. ### 3. Run scripts in order ``` code/sgma1_1_landscape.R # primary landscape and alpha/beta diversity analyses code/sgma1_1_household.R # household predictor analyses and variance partitioning code/sgma1_1_antibiotic.R # antibiotic use analysis and mediation code/sgma1_1_targeted_DA_landscape.R # differential abundance vs. settlement intensity code/sgma1_1_targeted_DA_ecoli.R # differential abundance vs. drinking water …