Analysis scripts and data for brush cell identification project 🧬 Single-Cell Analysis of Brush Cells This repository contains scripts, analysis workflows, and supporting data for the identification and characterization of brush cells using single-cell RNA sequencing (scRNA-seq) data. Brush cells are rare epithelial chemosensory cells involved in mucosal immunity and signaling, and this project explores their molecular signatures and distribution across various tissues.
🔍 Project Objectives Identify distinct epithelial cell populations, including brush cells, using scRNA-seq datasets from mouse and human airway tissues.
Perform dimensionality reduction (PCA, UMAP), clustering, and marker gene analysis.
Visualize expression of key genes associated with brush cell identity.
Integrate and compare datasets across tissues (e.g., trachea, urethra).
🧪 Methods Used Data preprocessing and QC using Seurat (R)
Clustering and annotation based on canonical markers
Differential gene expression analysis
Visualization using ggplot2, Seurat, and Shiny
🛠 Tools & Technologies R (Seurat, tidyverse, dplyr)
Bash (for batch processing)
Git for version control
Microscopy validation (confocal, fluorescence)
📁 Repository Structure /data – Raw and processed datasets (if available or with instructions)
/scripts – R scripts for preprocessing, analysis, and visualization
/figures – Plots and result images
/docs – Notes, protocols, and references
👩🔬 Author Krupali Poharkar Postdoctoral Researcher Department of Anatomy and Cell Biology, JLU Giessen, Germany