To annotate the glia subpopulation to the multiple brain region dataset, we first converted R objects to H5AD files using zellkonverter (v.1.8.0; github.com/theislab/zellkonverter). We integrated the multi-brain region combined dataset26 with the glia subpopulation dataset25 using single-cell variational inference81 from scvi-tools (v.0.20.1)82 per glia subpopulation. After integration, we transferred the glia subpopulation annotations to the multi-brain region dataset with single-cell annotation using variational inference (scANVI83) from scvi-tools. We visualized the glia subpopulation clustering after removing batch effects from the PCA subspace with fastMNN from the batchelor package and applying t-distributed stochastic neighbor embedding using the scater package (v.1.28.0)79.
