Extended Data Fig. 1: scRNA-seq and Multiome data processing and analysis workflow and quality control.

(a) Number of cells at each step in the scRNA-seq and snMultiome data processing and analysis pipeline. The identification of doublets and low-quality cells and clusters is described in detail in Methods. The 10xv3 and 10x Multiome data were first QC-ed and analyzed separately. After initial clustering the datasets were combined and QC-ed again before and after integration. (b-c) Number of cells after each QC step in scRNA-seq (b) and snMultiome data (c). The color codes of QC steps correspond to the colored QC boxes in (a). (d) Number of cells from each FACS population in scRNA-seq data. (e-h) Box plots of gene detection (e) and QC score (f) for 10xv3, and gene detection (g) and number of unique fragments (h) for 10x Multiome, per cell across different cell classes and ages. In the box plots, the central line indicates the median value (gene count, QC score, or number of unique fragments per cell), the box spans the interquartile range (IQR; 25th–75th percentile), and the whiskers extend to 1.5 × IQR, with outliers plotted individually. The number of cells for 10xv3 in each subclass each age is shown in Supplementary Table 3, and the detail for 10x Multiome is shown in Supplementary Table 8.