Single-cell technologies nowadays give us easy and large-scale access to cell-state
observations on the transcriptomic and epigenomic level. Within the Human Cell Atlas Lung
Biological Network, we aim to identify the distribution of SARS-CoV-2 cell entry genes across
more than 1.1M transcriptomes from 164 individuals. In particular we can link variation in
age, gender and smoking status to cell-type specific expression. The underlying
transcriptome networks provide hypotheses on how infection rates differ across the
population and motivate targeted studies and perturbation experiments.