scRNA-seq data preprocessing
For each sample we obtained the unfiltered feature-barcode matrix by passing demultiplexed FASTQs to Cell Ranger v.6.0.1 ‘count’ command using default parameters and the prebuilt GRCh38 genome reference (no. GRCh38-2020-A), and Chemistry flag (Single Cell 5’ PE) for scRNA (data files available via the gene expression omnibus (accession no. GSE223972). Seurat 4.1.0 was used for all subsequent analyses. Cells were further filtered to maintain only those cells with <20% human mitochondrial DNA content and a minimum of at least 200 and maximum of 20,000 genes expressed. We constructed a Seurat object using the unfiltered feature-barcode matrix for each sample. Each sample was scaled and normalized using Seurat’s ‘SCTransform’ function to correct for batch effects (with parameters ’vars.to.regress = c(‘nCount_RNA’, ‘percent.mito’)’, variable.features 