Fig. 4: ERK target gene expression predicts history of ERK activation.
From: Deciphering the history of ERK activity from fixed-cell immunofluorescence measurements
a Single-cell regression showing the coefficient of determination (R2) of linear regression models that use ETGs to predict each ERK feature. 10-fold cross-validation was conducted to retrieve the best test-set model. This model was then fit on the full dataset. “All” indicates multiple regression models using all ETGs as predictors. b Scatter plots of single-cell regression models showing line of best fit. Color indicates relative density of the data. c Scatter plot showing each cell’s predicted (x-axis) vs true (y-axis) value in the multiple linear regression (MLR) models. d Results of adding predictors to MLR models. Color of each point indicates which predictor was added at each step. e Average values were calculated for all cells with the same condition. These values were then used to fit regression models that predict each ERK feature using ETGs. f Scatter plots showing line of best fit and confidence intervals for condition average regression models. Each dot indicates the average of one condition.
