Description Usage Arguments Details Value Author(s) References See Also Examples
Produces a one page report depicting the results of a full BRAID analysis for a single combination.
1 | makeBRAIDreport(brdAnalysis, compounds, iaelevs, macs, control = list())
|
brdAnalysis |
a list representing the results of a full BRAID analysis, produced by the
|
compounds |
A two element character vector containing the names of the two compounds tested. Should be the same string repeated if combinaion is self-vs.-self |
iaelevs |
one or two effect levels at which the IAE and potentiation will be estimated |
macs |
the maximum achievable concentrations for the two compounds tested for the calculation of the IAE. If one concentration is provided, it will be used for both compounds. If combination is self-vs.-self the two concentrations must be equal. |
control |
A list of optional control parameters adjusting the appearance of the report see Details for a full description |
This is, by design, a rather massive function that attempts, however foolhardily, to consolidate all the pieces necessary to produce a comprehensive visualization and report on the results of a BRAID analysis. By default, it produces a one page report containing four rows of three panels. The first row contains a plot of the measured data passed to the BRAID fit, plotted without interpolation; a table of the best fit BRAID parameters, with confidence intervals; and tables of one or more IAE values (with confidence intervals), as determined by the given maximum achievable concentrations and either a purely additive surface or the best fit BRAID surface. The second row contains the measured data plotted with interpolation to convey the shape of the measured response surface; a plot of the predicted response surface assuming the measured dose-response behavior and BRAID additivity; and a plot of the best fit BRAID response surface. The third row contains a uninterpolated plot of the error resulting from simple smoothing (to provide a reasonable upper bound on quality of fit); a plot of the error resulting from a predicted additive surface (with R-squared value); and a plot of the error resulting from the best fit BRAID surface (with R-squared value). The fourth and final row shows potentiation in the best fit surface, containing tables of EC values for a specified threshold for each drug in the presence of various levels of the other; a potentiation plot of the first drug potentiated by the second; and the corresponding plot with the two drugs reversed. The theme settings and sizes are intended for use on a portrait-oriented 8.5 by 11 inch page.
Many details of the plots and report are adjusted by the control
parameter, which may
contain any or all of the following elements:
a boolean determining whether the function arranges the constructed plots and tables
and prints them to the existing graphics device. Doing so requires the package gridExtra
(version 2.0.0 or greater); if this package is not included, a warning will be printed and this
parameter will be reset to FALSE
. Default value is TRUE
a boolean determining whether the pieces generated for the report are returned as
a result of the function. This option can be used if the user wishes to arrange the plot him or
herself, rather than using the default layout approach. If TRUE
, the function returns a
list of fourteen objects; the nine ggplot
plots described above, followed by the five tables
assembled for the report. Note that the tables are returned as standard R arrays, not grid or
graphics objects. Using this option with plot
set to FALSE
does not require the
presence of gridExtra
. Default value is FALSE
a string or R expression to be used as the label of the modeled effect in all
plots. Default value is "Effect"
in axis labels and tables, the two drugs being combined are represented by abbreviations. By default these abbreviations consist of the first three characters of each compound name, with non alphanumeric characters removed. However, the user may wish to use custom abbreviations (e.g. "TMZ" for "temozolomide"); they may do so by specifying two abbreviations as two strings in this optional parameter.
an optional character vector the same length as iaelevs
, determining how
the corresponding levels will be displayed in tables. For example, if the modelled effect were
proportional cell survival, the user might want to specify a label of "90" for a modelled effect
of 0.1.
a boolean variable, passed to responseMap
, reflecting whether the
dose pairs being plotted lie on a regularly spaced grid. Default value is FALSE
a boolean variable, reflecting whether the concentration variables are plotted on a
logarithmic scale. This affects both the x- and y-axes in the seven surface plots, and the x-axis
in the TWO potentiation plots. Default value is TRUE
a boolean variable, reflecting whether the modeled effect is plotted on a
logarithmic scale. This affects only the y-axis in the two potentiaton plots. Default value is
FALSE
an optional function mapping the concentration of the first drug to the
transformed value that the user wishes to plot. A simple example would be one in which the fit was
performed on concentrations expressed in molar, but the user wishes to plot the concentrations in
micromolar, in which case the value of 'xtrans' might be function(x) x*10^6
.
an optional function mapping the concentration of the second drug to the transformed value that the user wishes to plot
a string or R expression (e.g. expression(mu*M)
) specifying how the units of
the first drug should be displayed in axis labels and tables. If not specified, units will be
omitted.
a string or R expression (e.g. expression(mu*M)
) specifying how the units of
the second drug should be displayed in axis labels and tables. If not specified, units will be
omitted.
an optional function mapping the modelled effect to the transformed value that the
user wishes to plot. An example might be a case in which the modelled effect variable is a
logarithmic transform of a real-world measurement, and the user wishes to plot the measured value,
in which case the value of 'ztrans' might be function(z) 10^z
.
a vector of two or more strings representing R colors, which will be passed to the
ggplot2
function scale_fill_gradientn
to specify the colormap for the plotted
response surfaces. If left unspecified, a modified version of the classic "jet" colorscale (with
dark green substituted for dark blue) will be used. Alternatively, if the user sets this parameter
to the string "gjet"
or "revgjet"
, the plots will use the modified "jet" colormap or
its reverse.
an optional size parameter passed to geom_point
to control the size
of plotted points
an optional size parameter passed to geom_line
to control the size
of plotted lines.
If the control
parameter return
is set TRUE
, a list of ggplot2
plots
and tables as described in the Description section above. If return
is set to FALSE
or omitted, the function returns NULL
.
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).
runBRAIDanalysis
, responseMap
, potentiationPlot
1 2 3 4 5 6 7 8 | data(es8analysis)
pcont<-list(xtrans=function(x) x*10^6,ytrans=function(y) y*10^6,ztrans=function(z) 10^z,
xunit=expression(mu*M),yunit=expression(mu*M),zlog=TRUE,abbs=c("Ola","TMZ"),
levtext=c("90","99"),palette="revgjet",plot=FALSE,return=TRUE)
brep <- makeBRAIDreport(es8analysis,c("Olaparib","Temozolomide"),
c(-1,-2),c(10^-6,5*10^-5),pcont)
brep[[1]]
brep[[10]]
|
Loading required package: ggplot2
Loading required package: braidrm
Warning messages:
1: `legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing
2: `legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing
3: `legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing
4: `legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing
5: `legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing
6: `legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing
7: `legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing
8: `legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing
9: `legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing
[,1]
ID['M,A'] "0.255 (0.236 - 0.28)"
ID['M,B'] "68.7 (63 - 76)"
n[a] "1.98 (1.73 - 2.3)"
n[b] "2.06 (1.77 - 2.32)"
E[0] "1.97 (1.65 - 2.32)"
E[f] "0.000149 (0.000128 - 0.000176)"
kappa "1.96 (1.44 - 2.49)"
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