scRNAseq-tutorial-MMG3003Y

Seurat-based scRNA-seq tutorial from MMG3003Y with annotated code and plots

This repository contains a personalized and annotated walkthrough of a guided Seurat tutorial from MMG3003Y (Genomics Methodologies) at the University of Toronto. The goal was to explore key steps in single-cell RNA-seq (scRNA-seq) analysis using real biological metadata and dimensionality reduction, clustering, and expression visualization.

🧬 Dataset

• Downsampled version of the Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD)
• Samples from the middle temporal gyrus (MTG), labeled by cognitive status and AD progression score

📁 Included Files

• annotated_scrnaseq_seurat_notes.Rmd: My personal annotated walkthrough of the Seurat pipeline
• figures/sc_violin_qc.png: Violin plot showing QC metrics (nFeature, nCount, mitochondrial%)
• figures/umap_clusters.png: UMAP plot of clustered cells with Seurat cluster IDs
• figures/feature_plot_top10.png: FeaturePlot of top 10 variable genes across clusters

🧰 Tools Used

• R, Seurat, SCTransform
• PCA, UMAP, Louvain clustering
• Feature and violin plots with ggplot2

📌 Notes

This work was adapted from in-class materials for personal learning and portfolio purposes. All code and reflections are original.