This repository contains scripts and templates for analyzing single-cell RNA sequencing (scRNA-seq) data. The pipeline processes 10X Genomics or Parse data through quality control, normalization, dimensionality reduction, clustering, cell type annotation, and differential expression analysis.
Start in the 03_Run folder and follow the sctipts in 00_scripts. This will walk through:
- Data Loading: Import 10X Genomics or Parse data
- Quality Control: Filter cells based on quality metrics
- Normalization: Using SCTransform or LogNormalize methods
- Dimensionality Reduction: PCA and UMAP visualization
- Integration (Optional): Batch effect correction
- Cell Type Annotation: Manual or automated (SingleR, scMRMA)
- Merging or Breaking Clusters (Optional): Based on reasercher's goals
- Differential Expression Analysis: Compare expression between groups
- R Shiny App Setup: The scRNA_shiny app for exporation of your data
The scRNAseq_Project.Rmd file serves as a template for creating comprehensive analysis reports. It pulls R objects created from the scripts and displays the information and figures in a rendered HTML file for the reasercher.