Single-cell analysis of cellular transcriptomes

Single cell analysis and cluster identification was performed on 1,654 – 16,903 captured cells per sample using the 10X Chromium single cell system (10X Genomics Inc.) at the University of Oklahoma Health Sciences Campus Genomics Core Facility and sequenced each sample to a read depth of 95-164K reads/cell, yielding 85-92% sequence saturation. Read mapping and expression quantification were performed using a combination of the 10X Cell Ranger pipeline (10X Genomics Inc.) and custom Seurat analytic scripts (74 (link)). Briefly, single-cell reads were mapped to the human genome (GRCH38) and assigned to genes using the standard Cell Ranger pipeline. Normalized gene expression was then used to produce a UMAP plot that provided cell clusters based on similarity of gene expression. Once cells were assigned to a cluster, custom Seurat scripts were used to statistically derive the gene expression differences within and between cell clusters using t-tests in Seurat. Trajectory analysis was then conducted using Monocle (75 (link)). To be statistically similar across the study, the Monocle trajectories were used to guide specific trajectory specific t-tests within Seurat. From these, pathway analyses were performed using Ingenuity Pathway Analysis (IPA, QIAGEN, Hilden, Germany) on the differential transcriptional profiles seen in the cell clusters and trajectory groups.