SingleCellRNASeqAnalysis

This project involves replicating and extending the findings of the Baron et al. study, which explores the cellular diversity in the human pancreas via single-cell RNA-Seq analysis.

Phases

1. Process Single Cell Sequencing Reads and Choose Barcodes: Processing barcode reads and performing cell-by-gene quantification of UMI counts.

2. Processing the UMI counts matrix: Filtering low-quality cells and genes from the UMI counts matrix and identifying clusters of cell type subpopulations.

3. Cluster Marker Genes: Identifying marker genes for each cluster, labeling clusters based on markers, and discovering novel marker genes.

4. In-depth Marker Gene Analysis: Conducting gene set enrichment analysis on the marker genes for each cluster.

5. Discuss Findings: Discussing findings with team members, comparing results to those in the Baron et al. study.

Prerequisites

Familiarity with single-cell RNA-Seq analysis, R language, and the Seurat package from Bioconductor is needed.

Contributing

You are encouraged to share and discuss strategies, and use any materials found online.

Authors

Ojong Tabi Lily Zandi Yuxiang Zhou ChihWei Fan

License

This project is licensed under the MIT License.

Acknowledgments

The work of Baron et al forms the basis of this project.