doseResponseCurve: Plot drug response curve of a given drug and a given cell for...

View source: R/doseResponseCurve.R

doseResponseCurveR Documentation

Plot drug response curve of a given drug and a given cell for a list of rSets (objects of the RadioSet class).

Description

Given a list of RadioSets, the function will plot the drug_response curve, for a given drug/cell pair. The y axis of the plot is the viability percentage and x axis is the log transformed Ds. If more than one rSet is provided, a light gray area would show the common concentration range between rSets. User can ask for type of sensitivity measurment to be shown in the plot legend. The user can also provide a list of their own Ds and viability values, as in the examples below, and it will be treated as experiments equivalent to values coming from a pset. The names of the concentration list determine the legend labels.

Usage

doseResponseCurve(
  rad.type = "radiation",
  cellline,
  rSets = list(),
  Ds = list(),
  SFs = list(),
  trunc = TRUE,
  legends.label = c("alpha", "beta", "rsquared"),
  ylim = c(0, 100),
  xlim,
  mycol,
  title,
  plot.type = c("Fitted", "Actual", "Both"),
  summarize.replicates = TRUE,
  lwd = 1,
  cex = 0.7,
  cex.main = 0.9,
  legend.loc = "topright",
  verbose = TRUE
)

Arguments

rad.type

'character(1)' The type(s) of radiation dosage to be plotted. If the plot is desirable for more than one radioset, A unique drug id should be provided.

cellline

'character(1)' A cell line name for which the radiation response curve should be plotted. If the plot is desirable for more than one radioset, a unique cell id should be provided.

rSets

'list' a list of RadioSet objects, for which the function should plot the curves.

Ds, SFs

'list' A list of Doses and SFs to plot, the function assumes that Ds[[i]] is plotted against SFs[[i]]. The names of the D list are used to create the legend labels

trunc

'logical(1)' Should the viability values be truncated to lie in [0-100] before doing the fitting

legends.label

'numeric' A vector of sensitivity measurment types which could be any combination of ic50_published, auc_published, auc_recomputed and auc_recomputed_star. A legend will be displayed on the top right of the plot which each line of the legend is the values of requested sensitivity measerments for one of the requested rSets. If this parameter is missed no legend would be provided for the plot.

ylim

'numeric' A vector of two numerical values to be used as ylim of the plot. If this parameter would be missed c(0,100) would be used as the ylim of the plot.

xlim

'numeric' A vector of two numerical values to be used as xlim of the plot. If this parameter would be missed the minimum and maximum concentrations between all the rSets would be used as plot xlim.

mycol

'numeric' A vector with the same lenght of the rSets parameter which will determine the color of the curve for the pharmaco sets. If this parameter is missed default colors from Rcolorbrewer package will be used as curves color.

title

'character' The title of the graph. If no title is provided, then it defaults to Drug':'Cell Line'.

plot.type

'character' Plot type which can be the actual one ("Actual") or the one fitted by logl logistic regression ("Fitted") or both of them ("Both"). If this parameter is missed by default actual curve is plotted.

summarize.replicates

'character' If this parameter is set to true replicates are summarized and replicates are plotted individually otherwise

lwd

'numeric' The line width to plot with

cex

'numeric' The cex parameter passed to plot

cex.main

'numeric' The cex.main parameter passed to plot, controls the size of the titles

legend.loc

And argument passable to xy.coords for the position to place the legend.

verbose

'logical(1)' Should warning messages about the data passed in be printed?

Value

Plots to the active graphics device and returns and invisible NULL.

Examples

doseResponseCurve(Ds=list("Experiment 1" = c(0, 2, 4, 6)),
  SFs=list("Experiment 1" = c(1,.6,.4,.2)), plot.type="Both")


bhklab/RadioGx documentation built on Oct. 6, 2023, 8:27 a.m.