Zlabel = "Loewe Synergy", fname = "plotly.html" ) 3+ Drug Combination SynergyĬurrently, only MuS圜, Loewe, Bliss, HSA, Combination Index, and Schindler can be used to calculate synergy of 3+ drug combinations. plot_surface_plotly ( xlabel = "Drug1", ylabel = "Drug2", \ plot_heatmap ( xlabel = "Drug1", ylabel = "Drug2" ) # Requires plotly model. synergy ) # Will have size equal to d1, d2, and E passed to fit() Visualize # Requires matplotlib model. fit ( df, df, df ) Get synergy values print ( model. read_csv ( "your_own_drug_response_data.csv" ) model = Loewe () model. from bination import Loewe # or Bliss, ZIP, HSA, Schindler, CombinationIndex import pandas as pd df = pd. E ( d1, d2 ) Nonparametric (dose dependent) synergy models Fit to data scatter_points is optional, but if given, it should be a pandas.DataFrame with (at least) columns "nc", "nc", and "effect". So for instance, if drug 1 is sampled at 0, 0.01, 0.1, 1, 10 uM (a total of 5 concentrations), and drug 1 is sampled at 0, 0.1, 1, 10 uM (a total of 4 concentrations), the doses and effects must cover all pairwise combinations ( e.g., 5*4=20 points must be given). Visualization requires the doses for drug 1 and drug 2 to be sampled on a complete rectangular grid. Ylabel = "Drug2", zlabel = "Effect", fname = "plotly.html", \ plot_surface_plotly ( df, df, xlabel = "Drug1", \ plot_heatmap ( df, df, xlabel = "Drug1", ylabel = "Drug2" ) # Requires plotly model. If the model was not fit with bootstrap_iterations, only the best fit value is used to determine synergism or antagonism. This will report any parameters that are synergistic or antagonistic across the entire requested confidence interval. Summarize synergy conclusions print ( model. If you request a 95% confidence interval, get_parameters() will calculate the 2.5% and 97.5% percentiles for each parameter. The full results of the bootstrapping are stored in model.bootstrap_parameters. Confidence intervals are only generated if you set the number of bootstrap_iterations in model.fit(). Read their documentation and publications to understand what they mean. get_parameters ( confidence_interval = 95 )Įach synergy model has their own synergy parameters. Get parameters + confidence intervals model. Each model has different parameters that may mean different things, so you may wish to check your choice model's _init_() arguments. fit ( df, df, df, bootstrap_iterations = 100 )īounds are optional, but will help the fitting algorithm if you know them. ncĪn example dataset can be found at from bination import MuS圜 # or BRAID, Zimmer import pandas as pd df = pd. InstallationĮxample Usage Parametric Models Fit to dataįor this, I assume you have access to a drug response data set that has (at least) the following columns. synergy - A Python library for calculating, analyzing, and visualizing drug combination synergy. Currently supports multiple models of synergy, including MuS圜, Bliss, Loewe, Combination Index, ZIP, Zimmer, BRAID, Schindler, and HSA. A python package to calculate, analyze, and visualize drug combination synergy and antagonism.
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