nonbranching pseudodynamics model  (MathWorks Inc)

Journal: Nature reviews. Genetics

Article Title: Statistical Mechanics meets Single Cell Biology

doi: 10.1038/s41576-021-00341-z

Figure Lengend Snippet: Algorithms and software for quantifying state-manifolds from scRNA-Seq data

Article Snippet: pseudodynamics , Drift-Diffusion PDE , MatLab , https://github.com/theislab/pseudodynamics , Fischer et al 59.

Techniques: Software

Journal: bioRxiv

Article Title: A time and single-cell resolved model of hematopoiesis

doi: 10.1101/2022.09.07.506735

Figure Lengend Snippet: (A) Diagramatic representation of megakaryocyte trajectory analysis with pseudodynamics. Following the arrows: putative cell transitions (pseudotime kernel) were used to estimate megakaryocyte cell fate, from which megakaryocyte trajectory was isolated (dashed line). Along the pseudotime cell densities were computed for each time-point (color-coded density profiles) and analyzed using the pseudodynamics framework providing differentiation and net proliferation rate estimates for each cell. (B) (left) UMAP projection of the HSPC landscape color- coded by cell fate probability of neutrophil lineage (estimated with pseudotime kernel, see A). Panels on the right show UMAP projections of isolated neutrophil trajectory color-coded by indicated parameters or gene expression. (C) Pseudodynamics fitted net proliferation parameter (red) and differentiation rate parameters (blue) along pseudotime for megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of genes differentially expressed around the region of interest shown in C. Left columns indicate genes belonging to enriched gene categories - E2F target (FDR <10 -38 ), G2-M checkpoint (FDR <10 -24 ) and cell cycle (FDR <10 -38 ). (E) Pseudodynamics fitted net proliferation (red) and differentiation rate (blue) parameters along pseudotime for neutrophil trajectory. Vertical lines indicate the region of interest. (F) Fitted gene expression values along pseudotime for neutrophil markers and two TF groups shown in (full analysis in ). Grey, dashed line indicated differentiation rates shown in E. Gene expression was scaled around the mean.

Article Snippet: To solve the PDE, we used the non-branching pseudodynamics model as compiled in MATLAB 2017b, with only one difference: we did not enforce differentiation to be 0 at the end of the trajectory which, together with the growth rates taking also negative values, accounts for the fact that the populations in our landscape are all transient and that fully mature cells are not captured by our gating strategy.

Techniques: Isolation, Gene Expression

Journal: bioRxiv

Article Title: A time and single-cell resolved model of hematopoiesis

doi: 10.1101/2022.09.07.506735

Figure Lengend Snippet: (A) UMAP projections of the HSPC landscape color-coded by cell fate probability for respective lineages (estimated with pseudotime kernel). (B) UMAP projections with cells selected for respective trajectories color-coded in blue. (C) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the megakaryocyte trajectory. Vertical lines indicate the region of interest. (D) Heatmap of TFs differentially expressed around the region of interest shown in C. (E) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the erythroid trajectory. Vertical lines indicate the region of interest. (F) Heatmap of TFs differentially expressed around the region of interest shown in E. (G) Pseudodynamics fitted net proliferation and differentiation rate parameters along pseudotime for the monocyte/dendritic cell trajectory. Vertical lines indicate the region of interest. (H) Heatmap of TFs differentially expressed around the region of interest shown in G.

Article Snippet: To solve the PDE, we used the non-branching pseudodynamics model as compiled in MATLAB 2017b, with only one difference: we did not enforce differentiation to be 0 at the end of the trajectory which, together with the growth rates taking also negative values, accounts for the fact that the populations in our landscape are all transient and that fully mature cells are not captured by our gating strategy.

Techniques: