p4ward.analyse.plot

p4ward.analyse.plot.interactive_plots(protacs: list[Protac], ligase_obj: Protein, receptor_obj: Protein, conf: object) → None

Runs the functions that generate the html for the interactive plots: plot_funnel, plot_ppi, plot_pca, plot_scatter. Then generates an overarching html file that combines these plots and writes this html to disk.

p4ward.analyse.plot.make_step_check(conf: object, protac_obj: Protac) → dict

Checks which modelling steps were run so that their results can be plotted (or not).

p4ward.analyse.plot.plot_funnel(ligase_obj: Protein, protac_obj: Protac, steps: dict) → str

Make the funnel interactive plot. This plot shows how many protein poses passed each filtering stage.

p4ward.analyse.plot.plot_pca(ligase_obj: Protein, receptor_obj: Protein, protac_obj: Protac, steps: dict) → str

Make PCA plot. This runs PCA on the triad coordinates of the protein poses, then plots PC1xPC2.

p4ward.analyse.plot.plot_ppi(ligase_obj: Protein, protac_obj: Protac, steps: dict) → str

Make the ppi distribution interactive plot. This shows, for each main filtering step, what is the distribution of the ppi scores.

p4ward.analyse.plot.plot_scatter(protac_obj: Protac) → str

Make scatter plot that shows ppi score vs protein-protac score. The datapoints are coloured according to rescore, if rescore was not calculated, then they are colored according to ppi score.