To explore cell-type populations, select from the list of featured publications popularly used to generate select organoids. You’ll be able to view the percentage breakdown of the various cell types identified within single-cell transcriptomic data from each published dataset. Alongside data from your selected publication, you will also be able to see data from organoids generated with various neural organoid STEMdiff™ kits.

In the second section, you will find cell cluster uniform manifold approximations and projections (UMAPs) for your selected publication, shown alongside a selection of neural organoid STEMdiff™ kits. UMAPs allow the visualization of high-dimensional data in a lower-dimensional space, typically 2D or 3D. These UMAPs cluster cells by scaling thousands of gene expression counts for each cell onto a 2D plot. Known markers from Birey at al. (2017) [Extended Data Figure 2d] were primarily used to determine the cell type identities of the main clusters. Additional markers from Tanaka et al. (2020) [Figure S1 B] were used to identify the primordial germ cells (PGC) population. You can also use the search feature to find the gene expression level of a specific gene of interest within each cell in the clustered UMAP.