Libraries corresponding to 13 donors were sequenced using Illumina NovaSeq S2 with a Read 1 26bp, Read 2 91bp, Index 1 8bp configuration before reads were aligned to GRCh38. Each sample was filtered individually for low quality cells and genes by analyzing distributions of reads, transcripts, percent reads mapped to mitochondrial genes, and complexity per cell, then merged as an outer join to create a single dataset. Clustering and differential expression tests were processed using Seurat v3.1.0 (https://satijalab.org/seurat/). Normalization and variable gene selection was processed with SCTransform (https://github.com/ChristophH/sctransform). Clustering for major cell types was performed using Louvain clustering on dimensionally reduced PCA space with resolution set via grid search optimizing for maximum average silhouette score. Due to the scale of the dataset, a randomized subsampling from across the dataset was used to calculate the silhouette score. We annotated clusters based on highly expressed genes, then sub-clusters were characterized by performing PCA dimensionality reduction and clustering over those cells alone, and annotated based on highly expressed genes found via one-versus-rest differential expression test (Wilcoxon) within the major cell type. Differential expression analysis between ACE2 + TMPRSS2 + and negative epithelial cells was performed in Seurat using a Wilcoxon test and Bonferroni p value correction. Expression data for epithelial cells included in this dataset can be visualized and downloaded here: https://singlecell.broadinstitute.org/single_cell/study/SCP812?scpbr=the-alexandria-project#study-summary.