responseMap: responseMap
In Michorlab/ACESO: A Cancer Evolution Simulation Optimizer

Description Usage Arguments Value Author(s) References See Also Examples

responseMap

1 2	responseMap(model, data, irreg = FALSE, interpolate = TRUE, margins = TRUE, logscale = TRUE, zlims = NULL, raster = TRUE)

`model`	a two-column array containing the values of input 1 and input 2 in each data point, or a symbolic formula (e.g. act ~ conc1+conc2) specifying which variables are to be visualized
`data`	if model is an array, a vector of values in response to inputs 1 and 2; if model is a formula, a data frame containing the columns specified in formula
`irreg`	reflects whether or not data points lie in a regularly-spaced grid in the space of data points to be plotted
`interpolate`	determines whether the plot will produce a smoothed response surface using Gaussian interpolation, or if the space will be visualized as a set of discrete measurements using nearest neighbor segmentation
`margins`	determines whether input pairs in which one of the two inputs is zero will be plotted; applies only to logarithmically scaled plots
`logscale`	determines whether the input variables will be plotted on a logarithmic scale, or a standard linear scale. Because this function is intended primarily for visualizing combined action dose-response, a logarithmic dose-pair space is the default.
`zlims`	an optional parameter specifying lower and upper bounds on the response variable. If present, all effect values outside the given range will be clipped to the minimum and maximum values
`raster`	by default, interpolated response surfaces will be rendered using the ggplot2 function geom_raster, a faster and optimized raster image version of geom_tile. In certain settings, however, geom_raster can produce unusual appearance. Setting this parameter to FALSE will force the plot to be rendered using geom_tile.

A ggplot2 plot object, depicting the response variable (represented by the plot\'s \'fill\' variable) as a function of two inputs (the x- and y-dimensions).

Nathaniel R. Twarog

Twarog, N.R., Stewart, E., Vowell Hamill, C., and Shelat, A. BRAID: A Unifying Paradigm for the Analysis of Combined Drug Action. Scientific Reports In Press (2016).

braidReports::responseMap

## Not run: 
data(Dactolisib_Trametinib_combination)
growth_data<-net_growth_rate(Dactolisib_Trametinib_combination)
rmap <- responseMap(Net_growth~CONC+CONC2,GD,logscale=T)

ResponseSurface.plot(rmap,xl=expression(paste("[Dactolisib] (",mu,"M)", sep="")),
                    yl=expression(paste("[Trametinib] (",mu,"M)", sep="")),
                    zl="Net growth rate of \n sensitive cells",
                   palette=c("hotpink1","yellow","darkturquoise"))

## End(Not run)