Supplementary Figure 9: Pseudodynamics model fits to T-cell maturation data with diffusion pseudotime as cell state.
From: Inferring population dynamics from single-cell RNA-sequencing time series data
(a-b) Cross validation results (leave-one-time-point-out) of pseudodynamics fits on T-cell maturation with diffusion pseudotime as cell state. (a) Overall prediction error on withheld data by regularization parameter value omega. (b) Regularized log-likelihood value of prediction at held-out time point (prediction error) by regularization parameter value omega and time point. (c-i) Observed density, model fit to full data (simulation) and imputed density (simulation_cv) on T-cell lineage at a given time point. The cell state shown is the cell state used in the main text linearly scaled into the interval [0,0.9] and extended to 1. Accordingly, there are no observations in (0.9,1]. The imputed density is the model fit of a model trained on all remaining time points with a regularization parameter of 10 (leave-one-time-point-out cross validation). (c) E13.5, (d) E14.5, (e) E15.5, (f) E16.5, (g) E17.5, (h) E18.5, (i) P0. (j) Population size estimates. Observed (points) and simulated (line) total size of thymic hematopoietic compartment in a thymic lobe with 95% confidence interval on simulated data (shaded) and observed data with one standard deviation around the mean as error bars. The population size observations are based on 5 replicates for t = 12.5 to t = 17.5 and on two replicates for t = 18.5 and t = 19.5. Replicates are independent measurements based on separate thymus samples for t = 12.5 to 18.5 and are independent measurements based on the two lobes of a single thymus for t = 19.5.
