R code & workflow for the JDR paper on oral microbiota transplant in dogs. Covers 16S rRNA gene sequence processing (DADA2), analysis (phyloseq), statistics, and animated plots (gganimate).
Machine learning project using NHANES dataset to predict periodontitis prevalence and severity with model evaluation.
Single-cell RNA-seq analysis of periodontitis PBMC samples using Seurat. Performed quality control, dimensionality reduction (PCA, UMAP), clustering, marker gene identification, and immune cell annotation to characterize cellular heterogeneity in GSE174609.
ML benchmark predicting periodontitis severity from BRAR panoramic radiographs — leakage-audited splits, negative controls, calibrated image baselines
Oral metagenomic analysis of antimicrobial resistance genes associated with periodontitis
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