single-cell RNA-seq analysis using Seurat

Analysis code for single-cell RNA-Seq dataset using 10xGenomics platform, collaboration with Andrés Cruz-Herranz (Manuscript in preparation, result was presented in ECTRIMS 2018).

Analysis workflow

1. CellRanger for mapping and gene counting

• Mapping with reference genome, quantify gene expression (counting reads), and QC
• This is the script for run on QB3 cluster (UCSF cluster server)

2. Seurat (R package) for normalization and clustering

• Normalization of gene counts in each cell
• Discover cell clusters and identify cell types of each cluster.
• Comparison of change in cell number between different time-point.
• Differential gene expression analysis for cell sub-population.

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• Created by Kicheol Kim, PhD (Feb, 2018)
• Baranzini Lab. (https://github.com/baranzini-lab), Department of Neurology, UCSF