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BIGL (version 1.7.0)

Biochemically Intuitive Generalized Loewe Model

Description

Response surface methods for drug synergy analysis. Available methods include generalized and classical Loewe formulations as well as Highest Single Agent methodology. Response surfaces can be plotted in an interactive 3-D plot and formal statistical tests for presence of synergistic effects are available. Implemented methods and tests are described in the article "BIGL: Biochemically Intuitive Generalized Loewe null model for prediction of the expected combined effect compatible with partial agonism and antagonism" by Koen Van der Borght, Annelies Tourny, Rytis Bagdziunas, Olivier Thas, Maxim Nazarov, Heather Turner, Bie Verbist & Hugo Ceulemans (2017) .

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Version

Install

install.packages('BIGL')

Monthly Downloads

558

Version

1.7.0

License

GPL-3

Issues

1

Pull Requests

0

Stars

7

Forks

8

Maintainer

Maxim Nazarov

Last Published

March 8th, 2023

Functions in BIGL (1.7.0)

directAntivirals

Partial data with combination experiments of direct-acting antivirals
directAntivirals_ALL

Full data with combination experiments of direct-acting antivirals
fitMarginals

Fit two 4-parameter log-logistic functions for a synergy experiment
fitSurface

Fit response surface model and compute meanR and maxR statistics
fitted.ResponseSurface

Predicted values of the response surface according to the given null model
df.residual.MarginalFit

Residual degrees of freedom in marginal model estimation
fitted.MarginalFit

Compute fitted values from monotherapy estimation
generalizedLoewe

Compute combined predicted response from drug doses according to standard or generalized Loewe model.
contour.ResponseSurface

Method for plotting of contours based on maxR statistics
generateData

Generate data from parameters of marginal monotherapy model
getR

Helper functions for the test statistics
get.summ.data

Summarize data by factor
get.abs_tval

Return absolute t-value, used in optimization call in optim.boxcox
getCP

Estimate CP matrix from bootstraps
initialMarginal

Estimate initial values for fitting marginal dose-response curves
isobologram

Isobologram of the response surface predicted by the null model
maxR

Compute maxR statistic for each off-axis dose combination
outsidePoints

List non-additive points
getTransformations

Return a list with transformation functions
plot.ResponseSurface

Method for plotting response surface objects
getd1d2

A function to get the d1d2 identifier
plot.MarginalFit

Plot monotherapy curve estimates
plot.BIGLconfInt

Plot confidence intervals in a contour plot
harbronLoewe

Alternative Loewe generalization
meanR

Compute meanR statistic for the estimated model
marginalOptim

Fit two 4-parameter log-logistic functions with common baseline
marginalNLS

Fit two 4-parameter log-logistic functions with non-linear least squares
hsa

Highest Single Agent model
plotMeanVarFit

Make a mean-variance plot
plotResponseSurface

Plot response surface
modelVar

Calculate model variance, assuming variance increases linearly with mean
optim.boxcox

Find optimal Box-Cox transformation parameters
predictOffAxis

Compute off-axis predictions
plotConfInt

Plot confidence intervals from BIGL object in a contour plot
predict.MarginalFit

Predict values on the dose-response curve
plot.meanR

Plot bootstrapped cumulative distribution function of meanR null distribution
runBIGL

Run the BIGL application for demonstrating response surfaces
print.summary.BIGLconfInt

Print summary of BIGLconfInt object
predictResponseSurface

Predict the entire response surface, so including on-axis points, and return the result as a matrix. For plotting purposes.
sampleResids

Sample residuals according to a new model
predictVar

Predict variance
plot.maxR

Plot of maxR object
plot.effect-size

Plot of effect-size object
print.summary.MarginalFit

Print method for summary of MarginalFit object
print.summary.maxR

Print summary of maxR object
print.summary.ResponseSurface

Print method for the summary function of ResponseSurface object
vcov.MarginalFit

Estimate of coefficient variance-covariance matrix
summary.meanR

Summary of meanR object
summary.ResponseSurface

Summary of ResponseSurface object
print.summary.meanR

Print summary of meanR object
residuals.MarginalFit

Residuals from marginal model estimation
summary.maxR

Summary of maxR object
summary.BIGLconfInt

Summary of confidence intervals object
summary.MarginalFit

Summary of MarginalFit object
simulateNull

Simulate data from a given null model and monotherapy coefficients
scaleResids

Functions for scaling, and rescaling residuals. May lead to unstable behaviour in practice
backscaleResids

Backscale residuals
Blissindependence

Bliss Independence Model
col2hex

R color to RGB (red/green/blue) conversion.
coef.MarginalFit

Coefficients from marginal model estimation
boxcox.transformation

Apply two-parameter Box-Cox transformation
L4

4-parameter logistic dose-response function
bootConfInt

Obtain confidence intervals for the raw effect sizes on every off-axis point and overall
addResids

Add residuals by adding to mean effects
constructFormula

Construct a model formula from parameter constraint matrix
GetStartGuess

Estimate initial values for dose-response curve fit