Fig. 3: Trajectory inference with STORIES in axolotl neuron regeneration.
From: STORIES: learning cell fate landscapes from spatial transcriptomics using optimal transport
a, Three-dimensional (3D) representation of the potential landscape learned with STORIES. The x and y axes are Isomap coordinates, and the z axis is an interpolation of the potential. Colors represent cell types involved in the regeneration process. b, Visual representation of cell–cell transitions computed using CellRank from STORIES’s velocity vectors. c, Two-dimensional (2D) visualization of an axolotl slice at 15 dpi, with cells colored by their cell-type annotation. d, 2D visualization of an axolotl slice at 15 dpi, with reaEGCs colored by their predicted fate probabilities for mpEX, dpEX and npxTX fates, from left to right. e, Smoothed gene expression for Vim and Nptx1 along the potential computed by STORIES. The blue line is a spline regression of expression from potential. f, Normalized gene expression regressed using a spline model along the potential computed by STORIES. Genes are ordered by the potential for which they achieve maximum expression. g, Smoothed gene expression for Hes5 and Nsg2 along the potential computed by STORIES. The blue line is a spline regression of expression from potential. h, Enrichment scores of transcription factors targeting candidate driver genes. A one-sided Wilcoxon rank-sum test is used to report P values.
