Fig. 3: Application of pseudo-time-space (PSTS) analysis to embryonic mouse brain development and human breast cancer metastasis.
a Mapping of PSTS values for radial glia and neurons onto the embryonic brain (sci-Space data33, 15,466 cells). The embryonic brain region is outlined in red (left). b PSTS branching processes in the context of neuronal migration during brain development. Neurons and radial glia are coloured orange and green, respectively, with branching arrows indicating the developmental trajectories predicted by PSTS. c Spatial-PAGA graph result showing sub-cluster connectivity in a human breast cancer tissue section. d Visualisation of PSTS values across the breast cancer tissue array (3813 spots for one Visium breast cancer tissue section). e PSTS prediction of metastasis from DCIS (ductal carcinoma in situ; pink clusters) to IDC (invasive ductal carcinoma; cyan clusters) by graph optimisation, and finding the optimal ω parameter to combine physical distance and gene expression (pseudotime; see also Fig. S10). H& E images to the right are magnifications of the two branches of the reconstructed trajectory, showing separate IDC lesion sub-clusters in different stages of invasion, with either a ’no cancer’ (top) or cancer (bottom) cell appearance. f Non-spatial pseudotime analysis (top), suggesting non-significant and/or noisy trajectories that connect all nodes (each node is a subcluster); only PSTS can show three independent cancer progression clades (bottom).
