Data for human single-cell parotid gland transcriptomics were obtained from the GEO database with accession number GSE188478 (Chen et al. 2021). This was then processed using CellRanger 7.0.1 (available from the 10X Genomics website). Clustering, annotation and analysis were performed using the R Seurat 4.1 package (Hao et al. 2021). We excluded cells with over 20,000 reads and under genes 500, and performed clustering based on the top most variable 2000 genes. The complete workflow, including data download, Cell Ranger processing and R scripts for Seurat, along with the corresponding CellRanger and reduced Seurat output files, is available in the following Zenodo repository (doi: 10.5281/zenodo.7470666). All analyzes were performed using a r5a.4xlarge AWS instance, with a total runtime of under 3 hours. Underlaying data used here: - `filtered_feature_bc_matrix.h5` : Filtered feature-barcode matrices from CellRanger - `raw_feature_bc_matrix.h5` : Unfiltered feature-barcode matrices from CellRanger. - `dieted.RDS` : is a reduced version of the original Seurat object, which lacks the ScaleData slot, as this extends it to over 6Gb. This can be reconstructed ruthnning `dieted <- ScaleData( dieted , features = rownames(dieted) )` after importing. - `digene_expression.csv`: Relative gene expression by cluster. - `Figure 2 data.xlsx`: Relative gene expression by cluster, normalized, for CFTR, acinar markers (AMY1A, ANO1 and AQP5) and ionocyte markers (SCNN1A, SLC4A11, KCNMA1 and FOXI1). Source data not included: - `GSE188478` : Transcriptomic Mapping for Human Parotid Gland at Single-Cell Resolution, from Chen et al. (2022). Available at the GEO database. - `refdata-gex-GRCh38-2020-A.tar.gz` : human genome reference. Available from 10X Genomics at https://cf.10xgenomics.com/supp/cell-exp/refdata-gex-GRCh38-2020-A.tar.gz