Fig. 5: PRESCIENT predicts the outcome of transcription factor perturbations in a large perturbational screen as well as the different effects of perturbations in early progenitors vs. cells further along endocrine induction. | Nature Communications

Fig. 5: PRESCIENT predicts the outcome of transcription factor perturbations in a large perturbational screen as well as the different effects of perturbations in early progenitors vs. cells further along endocrine induction.

From: Generative modeling of single-cell time series with PRESCIENT enables prediction of cell trajectories with interventions

Fig. 5

a Perturbational screen (z = 5) of all the TFs in the highly variable gene set of in vitro β-cell differentiation. The x-axis is the log2 fold-change (FC) of the final cell-type fraction of the target cell fraction between perturbed and unperturbed simulations. The y-axis is the -log10 p values of two-sided paired t-tests between target cell fate outcomes between unperturbed and perturbed simulations over n = 10 randomly sampled starting populations at the final time step consisting of 200 cells each. Points are colored if they are a hit (FDR < 0.01 and log2(FC) > 0.5) and β-cell fractions are shown in purple, α-cells in red, and EC-cells in blue. b Difference in final β-cell populations when introducing perturbations (z = 5) in different cell populations for different TFs. c Difference in final α-cell perturbations when introducing perturbations (z = 5) in different cell populations for different TFs. In b, c, different starting populations correspond to cell stages as labeled by Veres et al.: SOX2+ progenitors (progsox2), NKX61+ progenitors (prognkx61), and cells with early/middle/late NEUROG3 signatures (neurog3early, neurog3mid, neurog3late, respectively). Bar plots show average paired differences over n = 10 randomly sampled cell populations of 200 cells from each early subpopulation with error bars representing the 95% CI. Figure S4e, f show boxplots of this data.

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