Finally, we found that community-scale integration can substantially improve the identification of differentially expressed (DE) cell-type markers. The use of 19 study replicates specifically enables us to identify genes that show consistent patterns across laboratories and technologies, representing robust and reproducible markers. We grouped cells by both sample replicate and cell type identity, and performed differential expression on the resulting pseudobulk profiles (Fig. 4e and Supplementary Fig. 6). For example, we identified 116 positive markers for pulmonary ionocytes, representing one of the deepest transcriptional characterizations of this cell type. These markers included both canonical markers such as the transcription factor FOXI1, but also revealed clear ontology enrichments for ATPases (e.g. ATP6V1G3, ATP6V0A4) and chloride channels (e.g. CLCNKA, CLCNKB, CFTR), supporting the role of these cells in regulating chemical concentrations in the lung (Fig. 4f). One advantage of working with pseudobulk values is increased quantification accuracy for lowly expressed genes. Indeed, we repeatedly found that top DE markers found using this strategy tended to capture more genes at a lower range of average expression values (Fig. 4g).
