Project Description

This project seeks to replicate the primary findings of the paper “A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-Cell Population Structure.” by Barom M. et al by using sequencing data from a single human donor in order to perform cell-by-gene quantification and quality control on UMI counts as well as identify clusters marker genes for distinct cell type populations.

Contributors

Luke Zhang, Benyu Zhou, Sri Veerisetti and Mano Ranaweera

Repository Contents and the Order in which to run them

1. whitelist.qsub: Outputs read counts for each distinct barcode
2. filter.py: Filters barcodes by read count threshold
3. salmonindex.qsub: Creates Salmon Index
4. salvein.qsub: Runs Salmon Alvein
5. programmer.R: Read the Alevin matrix into Seurat and filter out low quality cells. Cells are clustered based on PCA result of high variance features.
6. Analyst.R: Labeling clusters and identifying marker genes for each cluster
7. Biologist.R: Filter cluster .csv files via wo criteria: p_val_adj < 0.05 and avg_log2FC > 0 and perform DAVID analysis