Comprehensive Single-Cell RNA-Seq Analysis

Base calls from sequencing were converted into fastq format using Illumina’s bcl2fastq program and demultiplexed by the University of Washington sequencing core. Reads were adaptor-clipped using trim_galore with default settings. Trimmed reads were mapped to the human reference genome (GRch38) using the STAR program (version 2.5.2b). Uniquely mapping reads were extracted, and duplicates were removed based on unique molecular identifier (UMI) sequences. To generate expression matrices, the number of UMIs for each cell mapping to the exonic and intronic regions of each gene was calculated. Potential ambient RNA reads were estimated and removed using the R package SoupX [38 (link)]. Doublets were then identified using the Python package Scrublet [39 (link)]. Further analysis for quality filtering was performed using the Seurat R package (version 3.2.2). Only cells with a total read count <10,000 and number of genes detected >100 were kept. To remove potential dead cells from the analysis, cells with >15% mitochondrial reads were filtered out. In total, we obtained 82,133 cells from 4 conditions.