Code-for-Single-Cell-Analysis

Single-Cell Analysis of Type 2 Diabetes Islet Data

This repository contains code and analysis for single-cell RNA sequencing (scRNA-seq) data from islet cells in individuals with Type 2 diabetes (T2D). The analysis is performed using data from the PANDB database, focusing on clustering, pseudotime analysis, and visualization. This is an on going project.

Features

• Raw Data download: Islet cell data download from PANCB database.
• Quality control and mapping : quality control and mapping performed by fastp and salmon.
• Count matrix Generation: Performed using tx2gene in R environment.
• Data Processing: Preprocessing and normalization of scRNA-seq data.
• Clustering: Identification of cell clusters using t-SNE and Seurat.
• Pseudotime Analysis: Inference of cell trajectories and pseudotime using Slingshot.
• Visualization: Generation of t-SNE plots and pseudotime trajectory plots.

Installation

To run the analysis, you need to have R and Linux/UNIX enviironment, the following pacakges are needed:

fastp, salmon, tximport, GenomicFeatures, bioconductor, rhdf5, DESeq2, SIngleCellExperiment, biomaRt, Seurat, cowplot, dplyr, ggplot2, slingshot, monocle3, SeuratWrappers

Results

The project generates various visualizations, including t-SNE plots and pseudotime trajectory plots, which can help in understanding the cellular heterogeneity and lineage relationships in islet cells of T2D patients.

Exmaple Results

• Violin plots of genes of interest
• PCA plots
• PCA illustrating key features that contribute to each principal component
• t-SNE cluster plots for cell identification
• t-SNE clusters highlighting genes of interest

Script definition

• pancdb_Final_26_T2D_scRNA: Bash script mass downloading raw scRNA-seq data from ftp links
• Cleaning+Alignment: Cleaning and aligning all raw data
• CleaningAlignentReference: Main script used for downloading and processing large scale scRNA-seq data
• Creating-tx2gene: Generating count matrix and saving data for further processing
• Exploring-Count-Matrix: Main script for generating figures and understanding the heterogeneity of beta cell failure in type 2 diabetes

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your changes. Ensure your code adheres to the project's coding standards and includes appropriate documentation.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For questions or feedback, please contact jonanzule@gmail.com.