R/release_profile_plot.R
In shirewoman2/Consultancy: Standardized tools for using R within the Simcyp Consultancy Team
Defines functions
release_profile_plot
Documented in
release_profile_plot
#' Make a graph of the release profiles of a compound
#'
#' \code{release_profile_plot} is meant to be used in conjunction with
#' \code{\link{extractExpDetails}} to create graphs with release-profile data,
#' possibly for multiple simulations or for multiple compounds.
#'
#' @param figure_type the type of figure to plot. \describe{
#'
#' \item{"means only"}{(default) show only the mean release profile}
#'
#' \item{"percentile ribbon"}{show an opaque line for the mean data and
#' transparent shading for the standard deviation.}}
#' @param linear_or_log the type of graph to be returned. Options: \describe{
#' \item{"semi-log"}{y axis is log transformed; this is the default}
#'
#' \item{"linear"}{no axis transformation}
#'
#' \item{"both vertical"}{both the linear and the semi-log graphs will be
#' returned, and graphs are stacked vertically}
#'
#' \item{"both horizontal"}{both the linear and the semi-log graphs will be
#' returned, and graphs are stacked horizontally}}
#' @param colorBy_column (optional) the column in
#' \code{existing_exp_details$ReleaseProfiles} that should be used for
#' determining which color lines and/or points will be. This should be
#' unquoted, e.g., \code{colorBy_column = Tissue}.
#' @param color_labels optionally specify a character vector for how you'd like
#' the labels for whatever you choose for \code{colorBy_column} to show up in
#' the legend. For example, use \code{color_labels = c("file 1.xlsx" = "fa
#' 0.5", "file 2.xlsx" = "fa 0.2")} to indicate that "file 1.xlsx" is for an
#' fa of 0.5 and "file 2.xlsx" is for an fa of 0.2. The order in the legend
#' will match the order designated here.
#' @param legend_label_color optionally indicate on the legend something
#' explanatory about what the colors represent. For example, if
#' \code{colorBy_column = File} and \code{legend_label_color = "Simulations
#' with various fa values"}, that will make the label above the file names in
#' the legend more explanatory than just "File". The default is to use
#' whatever the column name is for \code{colorBy_column}. If you don't want a
#' label for this legend item, set this to "none".
#' @param color_set the set of colors to use. Options: \describe{
#'
#' \item{"default"}{a set of colors from Cynthia Brewer et al. from Penn State
#' that are friendly to those with red-green colorblindness. The first three
#' colors are green, orange, and purple. This can also be referred to as
#' "Brewer set 2". If there are only two unique values in the colorBy_column,
#' then Brewer set 1 will be used since red and blue are still easily
#' distinguishable but also more aesthetically pleasing than green and
#' orange.}
#'
#' \item{"Brewer set 1"}{colors selected from the Brewer palette "set 1". The
#' first three colors are red, blue, and green.}
#'
#' \item{"ggplot2 default"}{the default set of colors used in ggplot2 graphs
#' (ggplot2 is an R package for graphing.)}
#'
#' \item{"rainbow"}{colors selected from a rainbow palette. The default
#' palette is limited to something like 6 colors, so if you have more than
#' that, that's when this palette is most useful. It's \emph{not} very useful
#' when you only need a couple of colors.}
#'
#' \item{"blue-green"}{a set of blues fading into greens. This palette can be
#' especially useful if you are comparing a systematic change in some
#' continuous variable -- for example, increasing dose or predicting how a
#' change in intrinsic solubility will affect concentration-time profiles --
#' because the direction of the trend will be clear.}
#'
#' \item{"blues"}{a set of blues fading light blue to dark blue. Like
#' "blue-green", this palette can be especially useful if you are comparing a
#' systematic change in some continuous variable.}
#'
#' \item{"Tableau"}{uses the standard Tableau palette; requires the "ggthemes"
#' package}
#'
#' \item{"viridis"}{from the eponymous package by Simon Garnier and ranges
#' colors from purple to blue to green to yellow in a manner that is
#' "printer-friendly, perceptually uniform and easy to read by those with
#' colorblindness", according to the package author}
#'
#' \item{a character vector of colors}{If you'd prefer to set all the colors
#' yourself to \emph{exactly} the colors you want, you can specify those
#' colors here. An example of how the syntax should look: \code{color_set =
#' c("dodgerblue3", "purple", "#D8212D")} or, if you want to specify exactly
#' which item in \code{colorBy_column} gets which color, you can supply a
#' named vector. For example, if you're coloring the lines by the compound ID,
#' you could do this: \code{color_set = c("substrate" = "dodgerblue3",
#' "inhibitor 1" = "purple", "primary metabolite 1" = "#D8212D")}. If you'd
#' like help creating a specific gradation of colors, please talk to a member
#' of the R Working Group about how to do that using
#' \link{colorRampPalette}.}}
#'
#' @param include_errorbars TRUE or FALSE (default) for whether to include error
#' bars for the standard deviation.
#' @param errorbar_width width of error bars to use in hours (or, if you've used
#' some other time unit, in whatever units are in your data). Default is 0.5.
#' @param linetype_column the column in
#' \code{existing_exp_details$ReleaseProfiles} that should be used for
#' determining the line types
#' @param linetype_labels optionally specify a character vector for how you'd
#' like the labels for whatever you choose for \code{linetype_column} to show
#' up in the legend. For example, use \code{linetype_labels = c("file 1.xlsx"
#' = "fa 0.5", "file 2.xlsx" = "fa 0.2")} to indicate that "file 1.xlsx" is
#' for an fa of 0.5 and "file 2.xlsx" is for an fa of 0.2. The order in the
#' legend will match the order designated here.
#' @param linetypes the line types to use. Default is "solid" for all lines.
#' You'll need one line type for each possible value in the column you
#' specified for \code{linetype_column}.
#' @param line_width optionally specify how thick to make the lines. Acceptable
#' input is a number; the default is 1 for most lines and 0.8 for some, to
#' give you an idea of where to start.
#' @param legend_label_linetype optionally indicate on the legend something
#' explanatory about what the line types represent. For example, if
#' \code{linetype_column = Inhibitor} and \code{legend_label_linetype =
#' "Inhibitor present"}, that will make the label in the legend above, e.g.,
#' "none", and whatever perpetrator was present more explanatory than just
#' "Inhibitor". The default is to use whatever the column name is for
#' \code{linetype_column}. If you don't want a label for this legend item, set
#' this to "none".
#' @param facet1_column optionally break up the graph into small multiples; this
#' specifies the first of up to two columns to break up the data by, and the
#' designated column name should be unquoted, e.g., \code{facet1_column =
#' Tissue}. If \code{floating_facet_scale} is FALSE and you haven't specified
#' \code{facet_ncol} or \code{facet_nrow}, then \code{facet1_column} will
#' designate the rows of the output graphs.
#' @param facet2_column optionally break up the graph into small multiples; this
#' specifies the second of up to two columns to break up the data by, and the
#' designated column name should be unquoted, e.g., \code{facet2_column =
#' CompoundID}. If \code{floating_facet_scale} is FALSE and you haven't
#' specified \code{facet_ncol} or \code{facet_nrow}, then
#' \code{facet2_column} will designate the columns of the output graphs.
#' @param facet_ncol optionally specify the number of columns of facetted graphs
#' you would like to have. This only applies when you have specified a column
#' for \code{facet1_column} and/or \code{facet2_column}.
#' @param facet_nrow optionally specify the number of rows of facetted graphs
#' you would like to have. This only applies when you have specified a column
#' for \code{facet1_column} and/or \code{facet2_column}.
#' @param floating_facet_scale TRUE or FALSE (default) for whether to allow the
#' axes for each facet of a multi-facetted graph to scale freely to best fit
#' whatever data are present. Default is FALSE, which means that all data will
#' be on the same scale for easy comparison. However, this could mean that
#' some graphs have lines that are hard to see, so you can set this to TRUE to
#' allow the axes to shrink or expand according to what data are present for
#' that facet. Floating axes comes with a trade-off for the looks of the
#' graphs, though: Setting this to TRUE does mean that your x axis won't
#' automatically have pretty breaks that are sensible for times in hours.
#' @param facet_spacing Optionally set the spacing between facets. If left as
#' NA, a best-guess as to a reasonable amount of space will be used. Units are
#' "lines", so try, e.g. \code{facet_spacing = 2}. (Reminder: Numeric data
#' should not be in quotes.)
#' @param time_range time range to display. Options: \describe{
#'
#' \item{NA}{entire time range of data; default}
#'
#' \item{a start time and end time in hours}{only data in that time range,
#' e.g. \code{c(24, 48)}. Note that there are no quotes around numeric data.}}
#'
#' @param x_axis_interval set the x-axis major tick-mark interval. Acceptable
#' input: any number or leave as NA to accept default values, which are
#' generally reasonable guesses as to aesthetically pleasing and PK-relevant
#' intervals.
#' @param x_axis_label optionally supply a character vector or an expression to
#' use for the x axis label
#' @param pad_x_axis optionally add a smidge of padding to the x axis (default
#' is TRUE, which includes some generally reasonable padding). If changed to
#' FALSE, the y axis will be placed right at the beginning of your time range
#' and all data will end \emph{exactly} at the end of the time range
#' specified. If you want a \emph{specific} amount of x-axis padding, set this
#' to a number; the default is \code{c(0.02, 0.04)}, which adds 2\% more space
#' to the left side and 4\% more space to the right side of the x axis. If you
#' only specify one number, padding is added to the left side.
#' @param pad_y_axis optionally add a smidge of padding to the y axis (default
#' is TRUE, which includes some generally reasonable padding). As with
#' \code{pad_x_axis}, if changed to FALSE, the x axis will be placed right at
#' the bottom of your data, possibly cutting a point in half. If you want a
#' \emph{specific} amount of y-axis padding, set this to a number; the default
#' is \code{c(0.02, 0)}, which adds 2\% more space to the bottom and nothing
#' to the top of the y axis. If you only specify one number, padding is added
#' to the bottom.
#' @param y_axis_limits_lin Optionally set the Y axis limits for the linear
#' plot, e.g., \code{c(10, 1000)}. If left as NA, the Y axis limits for the
#' linear plot will be automatically selected. This only applies when you have
#' requested a linear plot with \code{linear_or_log}.
#' @param y_axis_limits_log Optionally set the Y axis limits for the semi-log
#' plot, e.g., \code{c(10, 1000)}. Values will be rounded down and up,
#' respectively, to the nearest order of magnitude. If left as NA, the Y axis
#' limits for the semi-log plot will be automatically selected. This only
#' applies when you have requested a semi-log plot with \code{linear_or_log}.
#' @param y_axis_interval set the y-axis major tick-mark interval. Acceptable
#' input: any number or leave as NA to accept default values, which are
#' generally reasonable guesses as to aesthetically pleasing intervals.
#' @param y_axis_label optionally supply a character vector or an expression to
#' use for the y axis label
#' @param hline_position numerical position(s) of any horizontal lines to add to
#' the graph. The default is NA to have no lines, and good syntax if you
#' \emph{do} want lines would be, for example, \code{hline_position = 10} to
#' have a horizontal line at 10 ng/mL (or whatever your concentration units
#' are) or \code{hline_position = c(10, 100, 1000)} to have horizontal lines
#' at each of those y values. Examples of where this might be useful would be
#' to indicate a toxicity threshold, a target Cmin, or the lower limit of
#' quantification for the assay used to generate the concentration-time data.
#' @param hline_style the line color and type to use for any horizontal lines
#' that you add to the graph with \code{hline_position}. Default is "red
#' dotted", but any combination of 1) a color in R and 2) a named linetype is
#' acceptable. Examples: "red dotted", "blue dashed", or "#FFBE33 longdash".
#' To see all the possible linetypes, type \code{ggpubr::show_line_types()}
#' into the console.
#' @param vline_position numerical position(s) of any vertical lines to add to
#' the graph. The default is NA to have no lines, and good syntax if you
#' \emph{do} want lines would be, for example, \code{vline_position = 12} to
#' have a vertical line at 12 h or \code{vline_position = seq(from = 0, to =
#' 168, by = 24)} to have horizontal lines every 24 hours for one week.
#' Examples of where this might be useful would be indicating dosing times or
#' the time at which some other drug was started or stopped.
#' @param vline_style the line color and type to use for any vertical lines that
#' you add to the graph with \code{vline_position}. Default is "red dotted",
#' but any combination of 1) a color in R and 2) a named linetype is
#' acceptable. Examples: "red dotted", "blue dashed", or "#FFBE33 longdash".
#' To see all the possible linetypes, type \code{ggpubr::show_line_types()}
#' into the console.
#' @param graph_labels TRUE or FALSE for whether to include labels (A, B, C,
#' etc.) for each of the small graphs. (Not applicable if only outputting
#' linear or only semi-log graphs.)
#' @param graph_title optionally specify a title that will be centered across
#' your graph or set of graphs
#' @param graph_title_size the font size for the graph title if it's included;
#' default is 14. This also determines the font size of the graph labels.
#' @param legend_position Specify where you want the legend to be. Options are
#' "left", "right" (default in most scenarios), "bottom", "top", or "none" if
#' you don't want one at all.
#' @param prettify_compound_names set this to a) TRUE (default) or FALSE for
#' whether to make the compound names in the legend prettier or b) supply a
#' named character vector to set it to the exact name you'd prefer to see in
#' your legend. For example, \code{prettify_compound_names =
#' c("Sim-Ketoconazole-400 mg QD" = "ketoconazole", "Wks-Drug ABC-low_ka" =
#' "Drug ABC")} will make those compounds "ketoconazole" and "Drug ABC" in a
#' legend, and \code{prettify_compound_names = TRUE} will make some reasonable
#' guesses about what a prettier compound name should be. An example of
#' setting this to TRUE: "SV-Rifampicin-MD" would become "rifampicin", and
#' "Sim-Ketoconazole-200 mg BID" would become "ketoconazole".
#' @param existing_exp_details output from \code{\link{extractExpDetails}} or
#' \code{\link{extractExpDetails_mult}}. This must be from package version >=
#' 2.8.0.
#' @param save_graph optionally save the output graph by supplying a file name
#' in quotes here, e.g., "My conc time graph.png"or "My conc time graph.docx".
#' The nice thing about saving to Word is that the figure title and caption
#' text will be partly filled in automatically, although you should check that
#' the text makes sense in light of your exact graph. If you leave off ".png"
#' or ".docx", it will be saved as a png file, but if you specify a different
#' graphical file extension, it will be saved as that file format. Acceptable
#' graphical file extensions are "eps", "ps", "jpeg", "jpg", "tiff", "png",
#' "bmp", or "svg". Do not include any slashes, dollar signs, or periods in
#' the file name. Leaving this as NA means the file will not be automatically
#' saved to disk.
#' @param fig_height figure height in inches; default is 6
#' @param fig_width figure width in inches; default is 5
#'
#' @return a ggplot2 graphs or a set of arranged ggplot2 graphs
#' @export
#'
#' @examples
#' Details <- extractExpDetails_mult(sim_data_files = NA)
#'
#' release_profile_plot(existing_exp_details = Details)
#'
#' # If you have multiple simulations or multiple compounds and you only
#' # want to graph one, here is an example of how to filter your data to do
#' # that.
#'
#' Details_subset <- Details
#' Details_subset$ReleaseProfiles <- Details_subset$ReleaseProfiles %>%
#' filter(CompoundID == "substrate" &
#' File == "simulation A.xlsx")
#'
#' release_profile_plot(existing_exp_details = Details_subset)
#'
#'
release_profile_plot <- function(existing_exp_details,
sims_to_include = NA,
compoundsToExtract = NA,
figure_type = "percentile ribbon",
linear_or_log = "linear",
colorBy_column,
color_labels = NA,
legend_label_color = NA,
color_set = "default",
include_errorbars = FALSE,
errorbar_width = 0.5,
linetype_column,
linetype_labels = NA,
linetypes = c("solid", "dashed"),
line_width = NA,
line_transparency = NA,
legend_label_linetype = NA,
facet1_column,
facet2_column,
facet_ncol = NA,
facet_nrow = NA,
floating_facet_scale = FALSE,
facet_spacing = NA,
time_range = NA,
x_axis_interval = NA,
x_axis_label = NA,
pad_x_axis = TRUE,
pad_y_axis = TRUE,
y_axis_limits_lin = NA,
y_axis_limits_log = NA,
y_axis_interval = NA,
y_axis_label = "Percent released",
hline_position = NA,
hline_style = "red dotted",
vline_position = NA,
vline_style = "red dotted",
graph_labels = TRUE,
graph_title = NA,
graph_title_size = 14,
legend_position = NA,
prettify_compound_names = TRUE,
qc_graph = FALSE,
save_graph = NA,
fig_height = 6,
fig_width = 5){
# Error catching ---------------------------------------------------------
# Check whether tidyverse is loaded
if("package:tidyverse" %in% search() == FALSE){
stop("The SimcypConsultancy R package also requires the package tidyverse to be loaded, and it doesn't appear to be loaded yet. Please run `library(tidyverse)` and then try again.",
call. = FALSE)
}
if(figure_type %in% c("means only", "percentile ribbon") == FALSE){
warning("The only acceptable options for `figure_type` are `means_only` or `percentile ribbon`. We'll set this to the default, `percentile ribbon`.\n",
call. = FALSE)
figure_type <- "percentile ribbon"
}
if(is.na(y_axis_label)){
warning("You must specify a value for `y_axis_label`. We'll use the default value of `Percent released`.\n",
call. = FALSE)
y_axis_label <- "Percent released"
}
if(any(complete.cases(time_range)) && class(time_range) != "numeric"){
warning("For the `release_profile_plot` function, the time range may only be numeric or NA. We'll set this to NA.\n",
call. = FALSE)
time_range <- NA
}
# Need to harmonize input to check some of these other bits
existing_exp_details <- harmonize_details(existing_exp_details)
# If user has supplied regex, that should have length 1. If they supplied a
# character vector of files, that should probably have length > 1. Even if
# they only supplied a single file name here, it should still work to use
# regex instead of a perfect match.
if(any(complete.cases(sims_to_include)) &&
length(sims_to_include) == 1){
sims_to_include <- existing_exp_details$MainDetails$File[
str_detect(existing_exp_details$MainDetails$File,
sims_to_include)]
# At this point, sims_to_include should be a character vector of file
# names.
}
# Keeping only the requested sims for sims_to_include
if(any(complete.cases(sims_to_include))){
existing_exp_details <- filter_sims(which_object = existing_exp_details,
which_sims = sims_to_include,
include_or_omit = "include")
# existing_exp_details should now only have the sims they requested.
# Noting if any sims are missing.
MissingSims <- setdiff(sims_to_include,
existing_exp_details$MainDetails$File)
if(length(MissingSims) > 0){
warning(paste0("The following simulation files were not found in the ReleaseProfiles data for existing_exp_details:\n",
str_c(MissingSims, collapse = "\n"), "They will be ignored.\n"),
call. = FALSE)
}
} else {
sims_to_include <- unique(existing_exp_details$ReleaseProfiles$File)
}
if(all(is.na(compoundsToExtract))){
compoundsToExtract <- AllCompounds$CompoundID
}
# Checking for bad inputs on compounds
BadCmpd <- tolower(compoundsToExtract)[
which(tolower(compoundsToExtract) %in% AllCompounds$CompoundID == FALSE)]
GoodCmpd <- intersect(AllCompounds$CompoundID,
tolower(compoundsToExtract))
if(length(BadCmpd) > 0){
if(length(GoodCmpd) == 0){
stop(wrapn(paste0("None of the compounds you entered are among the possible options for compoundsToExtract: ",
str_comma(paste0("'", BadCmpd, "'")),
". Please check your inputs and try again.")),
call. = FALSE)
} else {
warning(wrapn(paste0("The following compounds are not among the possible options for compoundsToExtract: ",
str_comma(paste0("'", BadCmpd, "'")),
". They will be ignored.")),
call. = FALSE)
}
}
compoundsToExtract <- GoodCmpd
# Main body of function -------------------------------------------------
Release <- list()
for(ff in sims_to_include){
Release[[ff]] <- list()
Deets <- filter_sims(existing_exp_details,
which_sims = ff,
include_or_omit = "include")
for(cmpd in compoundsToExtract){
# Checking on whether compound was included in sim
if(as.logical(is.na(Deets$MainDetails[
AllCompounds$DetailNames[AllCompounds$CompoundID == cmpd]]))){
next
}
Suffix <- AllCompounds$Suffix[AllCompounds$CompoundID == cmpd]
# Different input data depending on the CR/MR input
if(complete.cases(Deets$MainDetails[[paste0("CR_MR_Input", Suffix)]]) &&
Deets$MainDetails[[paste0("CR_MR_Input", Suffix)]] ==
"Weibull"){
Release[[ff]][[cmpd]] <-
data.frame(CompoundID = cmpd,
Time = seq(from = 0,
to = Deets$MainDetails$SimDuration,
length.out = 500))
suppressWarnings(
Release[[ff]][[cmpd]]$Release_mean <-
pweibull(q = Release[[ff]][[cmpd]]$Time,
scale = Deets$MainDetails[[paste0("ReleaseProfile_alpha",
Suffix)]],
shape = Deets$MainDetails[[paste0("ReleaseProfile_beta",
Suffix)]]) *
Deets$MainDetails[[paste0("ReleaseProfile_Fmax", Suffix)]]
)
# I'm not clear on how to calculate the variation surrounding a
# weibull function, and this is giving me errors sometimes. Not
# showing anything but mean for Weibull release functions.
Release[[ff]][[cmpd]] <- Release[[ff]][[cmpd]] %>%
mutate(ReleaseUpper = Release_mean,
ReleaseLower = Release_mean)
# suppressWarnings(
# Release[[ff]][[cmpd]]$ReleaseUpper <-
# pweibull(q = Release[[ff]][[cmpd]]$Time,
#
# scale = Deets$MainDetails[[paste0("ReleaseProfile_alpha",
# Suffix)]] +
# Deets$MainDetails[[paste0("ReleaseProfile_alpha",
# Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_alpha_CV",
# Suffix)]],
#
# shape = Deets$MainDetails[[paste0("ReleaseProfile_beta",
# Suffix)]] +
# Deets$MainDetails[[paste0("ReleaseProfile_beta",
# Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_beta_CV",
# Suffix)]]) *
# (Deets$MainDetails[[paste0("ReleaseProfile_Fmax", Suffix)]] +
# Deets$MainDetails[[paste0("ReleaseProfile_Fmax", Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_Fmax_CV", Suffix)]])
# )
#
# suppressWarnings(
# Release[[ff]][[cmpd]]$ReleaseLower <-
# pweibull(q = Release[[ff]][[cmpd]]$Time,
#
# scale = Deets$MainDetails[[paste0("ReleaseProfile_alpha",
# Suffix)]] -
# Deets$MainDetails[[paste0("ReleaseProfile_alpha",
# Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_alpha_CV",
# Suffix)]],
#
# shape = Deets$MainDetails[[paste0("ReleaseProfile_beta",
# Suffix)]] -
# Deets$MainDetails[[paste0("ReleaseProfile_beta",
# Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_beta_CV",
# Suffix)]]) *
# (Deets$MainDetails[[paste0("ReleaseProfile_Fmax", Suffix)]] -
# Deets$MainDetails[[paste0("ReleaseProfile_Fmax", Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_Fmax_CV", Suffix)]])
# )
Release[[ff]][[cmpd]] <- Release[[ff]][[cmpd]] %>%
mutate(Release_mean = Release_mean / 100,
ReleaseUpper = ReleaseUpper / 100,
ReleaseLower = ReleaseLower / 100,
ReleaseSD = NA, # FIXME - return to this later. This isn't going to have conventional SD, so I want to use ReleaseUpper and ReleaseLower instead.
Tissue_subtype = NA,
Simulated = TRUE,
# placeholders only
Inhibitor = "none",
Trial = "mean",
Tissue = "plasma",
Conc_units = "ng/mL",
Time_units = "hours",
DoseNum = 1)
} else {
if(nrow(Deets$ReleaseProfiles %>% filter(CompoundID == cmpd)) == 0){next}
Release[[ff]][[cmpd]] <- Deets$ReleaseProfiles %>%
filter(CompoundID == cmpd) %>%
mutate(Release_mean = Release_mean / 100,
ReleaseUpper = Release_mean + Release_mean * Release_CV,
ReleaseLower = Release_mean - Release_mean * Release_CV,
ReleaseSD = Release_mean * Release_CV,
Tissue_subtype = NA,
Simulated = TRUE,
# placeholders only
Inhibitor = "none",
Trial = "mean",
Tissue = "plasma",
Conc_units = "ng/mL",
Time_units = "hours",
DoseNum = 1)
}
}
Release[[ff]] <- bind_rows(Release[[ff]])
}
Release <- bind_rows(Release)
# Adding compounds names
suppressMessages(
MyCompounds <- existing_exp_details$MainDetails %>%
select(any_of(c("File", "Substrate", "PrimaryMetabolite1",
"PrimaryMetabolite2", "SecondaryMetabolite",
"Inhibitor1", "Inhibitor1Metabolite",
"Inhibitor2"))) %>%
pivot_longer(cols = -File,
names_to = "DetailNames",
values_to = "Compound") %>%
left_join(AllCompounds) %>%
select(File, CompoundID, Compound) %>%
filter(complete.cases(Compound))
)
suppressMessages(
Release <- Release %>% left_join(MyCompounds)
)
# ggplot(Release, aes(x = Time, y = Release_mean,
# ymax = ReleaseUpper, ymin = ReleaseLower)) +
# geom_point() + geom_line() +
# geom_ribbon(alpha = 0.5) +
# scale_x_time() +
# theme_consultancy()
facet1_column <- rlang::enquo(facet1_column)
facet2_column <- rlang::enquo(facet2_column)
colorBy_column <- rlang::enquo(colorBy_column)
linetype_column <- rlang::enquo(linetype_column)
# Including hacks to make this work
ct_plot_overlay(
ct_dataframe = Release,
figure_type = figure_type,
# NSE trouble: not enquo alone, not quo, not
# substitute, but enquo plus !! here
colorBy_column = !!colorBy_column,
linetype_column = !!linetype_column,
facet1_column = !!facet1_column,
facet2_column = !!facet2_column,
obs_to_sim_assignment = NA,
mean_type = "arithmetic",
linear_or_log = linear_or_log,
color_labels = color_labels,
legend_label_color = legend_label_color,
color_set = color_set,
include_errorbars = include_errorbars,
errorbar_width = errorbar_width,
linetype_labels = linetype_labels,
linetypes = linetypes,
line_width = line_width,
line_transparency = line_transparency,
legend_label_linetype = legend_label_linetype,
facet_ncol = facet_ncol,
facet_nrow = facet_nrow,
floating_facet_scale = floating_facet_scale,
facet_spacing = facet_spacing,
time_range = time_range,
x_axis_interval = x_axis_interval,
x_axis_label = x_axis_label,
pad_x_axis = pad_x_axis,
pad_y_axis = pad_y_axis,
y_axis_limits_lin = y_axis_limits_lin,
y_axis_limits_log = y_axis_limits_log,
y_axis_interval = y_axis_interval,
y_axis_label = y_axis_label,
hline_position = hline_position,
hline_style = hline_style,
vline_position = vline_position,
vline_style = vline_style,
graph_labels = graph_labels,
graph_title = graph_title,
graph_title_size = graph_title_size,
legend_position = legend_position,
prettify_compound_names = prettify_compound_names,
qc_graph = FALSE,
existing_exp_details = existing_exp_details,
save_graph = save_graph,
fig_height = fig_height,
fig_width = fig_width)
}
shirewoman2/Consultancy documentation built on Feb. 18, 2025, 10 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions release_profile_plot
Documented in release_profile_plot
#' Make a graph of the release profiles of a compound
#'
#' \code{release_profile_plot} is meant to be used in conjunction with
#' \code{\link{extractExpDetails}} to create graphs with release-profile data,
#' possibly for multiple simulations or for multiple compounds.
#'
#' @param figure_type the type of figure to plot. \describe{
#'
#' \item{"means only"}{(default) show only the mean release profile}
#'
#' \item{"percentile ribbon"}{show an opaque line for the mean data and
#' transparent shading for the standard deviation.}}
#' @param linear_or_log the type of graph to be returned. Options: \describe{
#' \item{"semi-log"}{y axis is log transformed; this is the default}
#'
#' \item{"linear"}{no axis transformation}
#'
#' \item{"both vertical"}{both the linear and the semi-log graphs will be
#' returned, and graphs are stacked vertically}
#'
#' \item{"both horizontal"}{both the linear and the semi-log graphs will be
#' returned, and graphs are stacked horizontally}}
#' @param colorBy_column (optional) the column in
#' \code{existing_exp_details$ReleaseProfiles} that should be used for
#' determining which color lines and/or points will be. This should be
#' unquoted, e.g., \code{colorBy_column = Tissue}.
#' @param color_labels optionally specify a character vector for how you'd like
#' the labels for whatever you choose for \code{colorBy_column} to show up in
#' the legend. For example, use \code{color_labels = c("file 1.xlsx" = "fa
#' 0.5", "file 2.xlsx" = "fa 0.2")} to indicate that "file 1.xlsx" is for an
#' fa of 0.5 and "file 2.xlsx" is for an fa of 0.2. The order in the legend
#' will match the order designated here.
#' @param legend_label_color optionally indicate on the legend something
#' explanatory about what the colors represent. For example, if
#' \code{colorBy_column = File} and \code{legend_label_color = "Simulations
#' with various fa values"}, that will make the label above the file names in
#' the legend more explanatory than just "File". The default is to use
#' whatever the column name is for \code{colorBy_column}. If you don't want a
#' label for this legend item, set this to "none".
#' @param color_set the set of colors to use. Options: \describe{
#'
#' \item{"default"}{a set of colors from Cynthia Brewer et al. from Penn State
#' that are friendly to those with red-green colorblindness. The first three
#' colors are green, orange, and purple. This can also be referred to as
#' "Brewer set 2". If there are only two unique values in the colorBy_column,
#' then Brewer set 1 will be used since red and blue are still easily
#' distinguishable but also more aesthetically pleasing than green and
#' orange.}
#'
#' \item{"Brewer set 1"}{colors selected from the Brewer palette "set 1". The
#' first three colors are red, blue, and green.}
#'
#' \item{"ggplot2 default"}{the default set of colors used in ggplot2 graphs
#' (ggplot2 is an R package for graphing.)}
#'
#' \item{"rainbow"}{colors selected from a rainbow palette. The default
#' palette is limited to something like 6 colors, so if you have more than
#' that, that's when this palette is most useful. It's \emph{not} very useful
#' when you only need a couple of colors.}
#'
#' \item{"blue-green"}{a set of blues fading into greens. This palette can be
#' especially useful if you are comparing a systematic change in some
#' continuous variable -- for example, increasing dose or predicting how a
#' change in intrinsic solubility will affect concentration-time profiles --
#' because the direction of the trend will be clear.}
#'
#' \item{"blues"}{a set of blues fading light blue to dark blue. Like
#' "blue-green", this palette can be especially useful if you are comparing a
#' systematic change in some continuous variable.}
#'
#' \item{"Tableau"}{uses the standard Tableau palette; requires the "ggthemes"
#' package}
#'
#' \item{"viridis"}{from the eponymous package by Simon Garnier and ranges
#' colors from purple to blue to green to yellow in a manner that is
#' "printer-friendly, perceptually uniform and easy to read by those with
#' colorblindness", according to the package author}
#'
#' \item{a character vector of colors}{If you'd prefer to set all the colors
#' yourself to \emph{exactly} the colors you want, you can specify those
#' colors here. An example of how the syntax should look: \code{color_set =
#' c("dodgerblue3", "purple", "#D8212D")} or, if you want to specify exactly
#' which item in \code{colorBy_column} gets which color, you can supply a
#' named vector. For example, if you're coloring the lines by the compound ID,
#' you could do this: \code{color_set = c("substrate" = "dodgerblue3",
#' "inhibitor 1" = "purple", "primary metabolite 1" = "#D8212D")}. If you'd
#' like help creating a specific gradation of colors, please talk to a member
#' of the R Working Group about how to do that using
#' \link{colorRampPalette}.}}
#'
#' @param include_errorbars TRUE or FALSE (default) for whether to include error
#' bars for the standard deviation.
#' @param errorbar_width width of error bars to use in hours (or, if you've used
#' some other time unit, in whatever units are in your data). Default is 0.5.
#' @param linetype_column the column in
#' \code{existing_exp_details$ReleaseProfiles} that should be used for
#' determining the line types
#' @param linetype_labels optionally specify a character vector for how you'd
#' like the labels for whatever you choose for \code{linetype_column} to show
#' up in the legend. For example, use \code{linetype_labels = c("file 1.xlsx"
#' = "fa 0.5", "file 2.xlsx" = "fa 0.2")} to indicate that "file 1.xlsx" is
#' for an fa of 0.5 and "file 2.xlsx" is for an fa of 0.2. The order in the
#' legend will match the order designated here.
#' @param linetypes the line types to use. Default is "solid" for all lines.
#' You'll need one line type for each possible value in the column you
#' specified for \code{linetype_column}.
#' @param line_width optionally specify how thick to make the lines. Acceptable
#' input is a number; the default is 1 for most lines and 0.8 for some, to
#' give you an idea of where to start.
#' @param legend_label_linetype optionally indicate on the legend something
#' explanatory about what the line types represent. For example, if
#' \code{linetype_column = Inhibitor} and \code{legend_label_linetype =
#' "Inhibitor present"}, that will make the label in the legend above, e.g.,
#' "none", and whatever perpetrator was present more explanatory than just
#' "Inhibitor". The default is to use whatever the column name is for
#' \code{linetype_column}. If you don't want a label for this legend item, set
#' this to "none".
#' @param facet1_column optionally break up the graph into small multiples; this
#' specifies the first of up to two columns to break up the data by, and the
#' designated column name should be unquoted, e.g., \code{facet1_column =
#' Tissue}. If \code{floating_facet_scale} is FALSE and you haven't specified
#' \code{facet_ncol} or \code{facet_nrow}, then \code{facet1_column} will
#' designate the rows of the output graphs.
#' @param facet2_column optionally break up the graph into small multiples; this
#' specifies the second of up to two columns to break up the data by, and the
#' designated column name should be unquoted, e.g., \code{facet2_column =
#' CompoundID}. If \code{floating_facet_scale} is FALSE and you haven't
#' specified \code{facet_ncol} or \code{facet_nrow}, then
#' \code{facet2_column} will designate the columns of the output graphs.
#' @param facet_ncol optionally specify the number of columns of facetted graphs
#' you would like to have. This only applies when you have specified a column
#' for \code{facet1_column} and/or \code{facet2_column}.
#' @param facet_nrow optionally specify the number of rows of facetted graphs
#' you would like to have. This only applies when you have specified a column
#' for \code{facet1_column} and/or \code{facet2_column}.
#' @param floating_facet_scale TRUE or FALSE (default) for whether to allow the
#' axes for each facet of a multi-facetted graph to scale freely to best fit
#' whatever data are present. Default is FALSE, which means that all data will
#' be on the same scale for easy comparison. However, this could mean that
#' some graphs have lines that are hard to see, so you can set this to TRUE to
#' allow the axes to shrink or expand according to what data are present for
#' that facet. Floating axes comes with a trade-off for the looks of the
#' graphs, though: Setting this to TRUE does mean that your x axis won't
#' automatically have pretty breaks that are sensible for times in hours.
#' @param facet_spacing Optionally set the spacing between facets. If left as
#' NA, a best-guess as to a reasonable amount of space will be used. Units are
#' "lines", so try, e.g. \code{facet_spacing = 2}. (Reminder: Numeric data
#' should not be in quotes.)
#' @param time_range time range to display. Options: \describe{
#'
#' \item{NA}{entire time range of data; default}
#'
#' \item{a start time and end time in hours}{only data in that time range,
#' e.g. \code{c(24, 48)}. Note that there are no quotes around numeric data.}}
#'
#' @param x_axis_interval set the x-axis major tick-mark interval. Acceptable
#' input: any number or leave as NA to accept default values, which are
#' generally reasonable guesses as to aesthetically pleasing and PK-relevant
#' intervals.
#' @param x_axis_label optionally supply a character vector or an expression to
#' use for the x axis label
#' @param pad_x_axis optionally add a smidge of padding to the x axis (default
#' is TRUE, which includes some generally reasonable padding). If changed to
#' FALSE, the y axis will be placed right at the beginning of your time range
#' and all data will end \emph{exactly} at the end of the time range
#' specified. If you want a \emph{specific} amount of x-axis padding, set this
#' to a number; the default is \code{c(0.02, 0.04)}, which adds 2\% more space
#' to the left side and 4\% more space to the right side of the x axis. If you
#' only specify one number, padding is added to the left side.
#' @param pad_y_axis optionally add a smidge of padding to the y axis (default
#' is TRUE, which includes some generally reasonable padding). As with
#' \code{pad_x_axis}, if changed to FALSE, the x axis will be placed right at
#' the bottom of your data, possibly cutting a point in half. If you want a
#' \emph{specific} amount of y-axis padding, set this to a number; the default
#' is \code{c(0.02, 0)}, which adds 2\% more space to the bottom and nothing
#' to the top of the y axis. If you only specify one number, padding is added
#' to the bottom.
#' @param y_axis_limits_lin Optionally set the Y axis limits for the linear
#' plot, e.g., \code{c(10, 1000)}. If left as NA, the Y axis limits for the
#' linear plot will be automatically selected. This only applies when you have
#' requested a linear plot with \code{linear_or_log}.
#' @param y_axis_limits_log Optionally set the Y axis limits for the semi-log
#' plot, e.g., \code{c(10, 1000)}. Values will be rounded down and up,
#' respectively, to the nearest order of magnitude. If left as NA, the Y axis
#' limits for the semi-log plot will be automatically selected. This only
#' applies when you have requested a semi-log plot with \code{linear_or_log}.
#' @param y_axis_interval set the y-axis major tick-mark interval. Acceptable
#' input: any number or leave as NA to accept default values, which are
#' generally reasonable guesses as to aesthetically pleasing intervals.
#' @param y_axis_label optionally supply a character vector or an expression to
#' use for the y axis label
#' @param hline_position numerical position(s) of any horizontal lines to add to
#' the graph. The default is NA to have no lines, and good syntax if you
#' \emph{do} want lines would be, for example, \code{hline_position = 10} to
#' have a horizontal line at 10 ng/mL (or whatever your concentration units
#' are) or \code{hline_position = c(10, 100, 1000)} to have horizontal lines
#' at each of those y values. Examples of where this might be useful would be
#' to indicate a toxicity threshold, a target Cmin, or the lower limit of
#' quantification for the assay used to generate the concentration-time data.
#' @param hline_style the line color and type to use for any horizontal lines
#' that you add to the graph with \code{hline_position}. Default is "red
#' dotted", but any combination of 1) a color in R and 2) a named linetype is
#' acceptable. Examples: "red dotted", "blue dashed", or "#FFBE33 longdash".
#' To see all the possible linetypes, type \code{ggpubr::show_line_types()}
#' into the console.
#' @param vline_position numerical position(s) of any vertical lines to add to
#' the graph. The default is NA to have no lines, and good syntax if you
#' \emph{do} want lines would be, for example, \code{vline_position = 12} to
#' have a vertical line at 12 h or \code{vline_position = seq(from = 0, to =
#' 168, by = 24)} to have horizontal lines every 24 hours for one week.
#' Examples of where this might be useful would be indicating dosing times or
#' the time at which some other drug was started or stopped.
#' @param vline_style the line color and type to use for any vertical lines that
#' you add to the graph with \code{vline_position}. Default is "red dotted",
#' but any combination of 1) a color in R and 2) a named linetype is
#' acceptable. Examples: "red dotted", "blue dashed", or "#FFBE33 longdash".
#' To see all the possible linetypes, type \code{ggpubr::show_line_types()}
#' into the console.
#' @param graph_labels TRUE or FALSE for whether to include labels (A, B, C,
#' etc.) for each of the small graphs. (Not applicable if only outputting
#' linear or only semi-log graphs.)
#' @param graph_title optionally specify a title that will be centered across
#' your graph or set of graphs
#' @param graph_title_size the font size for the graph title if it's included;
#' default is 14. This also determines the font size of the graph labels.
#' @param legend_position Specify where you want the legend to be. Options are
#' "left", "right" (default in most scenarios), "bottom", "top", or "none" if
#' you don't want one at all.
#' @param prettify_compound_names set this to a) TRUE (default) or FALSE for
#' whether to make the compound names in the legend prettier or b) supply a
#' named character vector to set it to the exact name you'd prefer to see in
#' your legend. For example, \code{prettify_compound_names =
#' c("Sim-Ketoconazole-400 mg QD" = "ketoconazole", "Wks-Drug ABC-low_ka" =
#' "Drug ABC")} will make those compounds "ketoconazole" and "Drug ABC" in a
#' legend, and \code{prettify_compound_names = TRUE} will make some reasonable
#' guesses about what a prettier compound name should be. An example of
#' setting this to TRUE: "SV-Rifampicin-MD" would become "rifampicin", and
#' "Sim-Ketoconazole-200 mg BID" would become "ketoconazole".
#' @param existing_exp_details output from \code{\link{extractExpDetails}} or
#' \code{\link{extractExpDetails_mult}}. This must be from package version >=
#' 2.8.0.
#' @param save_graph optionally save the output graph by supplying a file name
#' in quotes here, e.g., "My conc time graph.png"or "My conc time graph.docx".
#' The nice thing about saving to Word is that the figure title and caption
#' text will be partly filled in automatically, although you should check that
#' the text makes sense in light of your exact graph. If you leave off ".png"
#' or ".docx", it will be saved as a png file, but if you specify a different
#' graphical file extension, it will be saved as that file format. Acceptable
#' graphical file extensions are "eps", "ps", "jpeg", "jpg", "tiff", "png",
#' "bmp", or "svg". Do not include any slashes, dollar signs, or periods in
#' the file name. Leaving this as NA means the file will not be automatically
#' saved to disk.
#' @param fig_height figure height in inches; default is 6
#' @param fig_width figure width in inches; default is 5
#'
#' @return a ggplot2 graphs or a set of arranged ggplot2 graphs
#' @export
#'
#' @examples
#' Details <- extractExpDetails_mult(sim_data_files = NA)
#'
#' release_profile_plot(existing_exp_details = Details)
#'
#' # If you have multiple simulations or multiple compounds and you only
#' # want to graph one, here is an example of how to filter your data to do
#' # that.
#'
#' Details_subset <- Details
#' Details_subset$ReleaseProfiles <- Details_subset$ReleaseProfiles %>%
#' filter(CompoundID == "substrate" &
#' File == "simulation A.xlsx")
#'
#' release_profile_plot(existing_exp_details = Details_subset)
#'
#'
release_profile_plot <- function(existing_exp_details,
sims_to_include = NA,
compoundsToExtract = NA,
figure_type = "percentile ribbon",
linear_or_log = "linear",
colorBy_column,
color_labels = NA,
legend_label_color = NA,
color_set = "default",
include_errorbars = FALSE,
errorbar_width = 0.5,
linetype_column,
linetype_labels = NA,
linetypes = c("solid", "dashed"),
line_width = NA,
line_transparency = NA,
legend_label_linetype = NA,
facet1_column,
facet2_column,
facet_ncol = NA,
facet_nrow = NA,
floating_facet_scale = FALSE,
facet_spacing = NA,
time_range = NA,
x_axis_interval = NA,
x_axis_label = NA,
pad_x_axis = TRUE,
pad_y_axis = TRUE,
y_axis_limits_lin = NA,
y_axis_limits_log = NA,
y_axis_interval = NA,
y_axis_label = "Percent released",
hline_position = NA,
hline_style = "red dotted",
vline_position = NA,
vline_style = "red dotted",
graph_labels = TRUE,
graph_title = NA,
graph_title_size = 14,
legend_position = NA,
prettify_compound_names = TRUE,
qc_graph = FALSE,
save_graph = NA,
fig_height = 6,
fig_width = 5){
# Error catching ---------------------------------------------------------
# Check whether tidyverse is loaded
if("package:tidyverse" %in% search() == FALSE){
stop("The SimcypConsultancy R package also requires the package tidyverse to be loaded, and it doesn't appear to be loaded yet. Please run `library(tidyverse)` and then try again.",
call. = FALSE)
}
if(figure_type %in% c("means only", "percentile ribbon") == FALSE){
warning("The only acceptable options for `figure_type` are `means_only` or `percentile ribbon`. We'll set this to the default, `percentile ribbon`.\n",
call. = FALSE)
figure_type <- "percentile ribbon"
}
if(is.na(y_axis_label)){
warning("You must specify a value for `y_axis_label`. We'll use the default value of `Percent released`.\n",
call. = FALSE)
y_axis_label <- "Percent released"
}
if(any(complete.cases(time_range)) && class(time_range) != "numeric"){
warning("For the `release_profile_plot` function, the time range may only be numeric or NA. We'll set this to NA.\n",
call. = FALSE)
time_range <- NA
}
# Need to harmonize input to check some of these other bits
existing_exp_details <- harmonize_details(existing_exp_details)
# If user has supplied regex, that should have length 1. If they supplied a
# character vector of files, that should probably have length > 1. Even if
# they only supplied a single file name here, it should still work to use
# regex instead of a perfect match.
if(any(complete.cases(sims_to_include)) &&
length(sims_to_include) == 1){
sims_to_include <- existing_exp_details$MainDetails$File[
str_detect(existing_exp_details$MainDetails$File,
sims_to_include)]
# At this point, sims_to_include should be a character vector of file
# names.
}
# Keeping only the requested sims for sims_to_include
if(any(complete.cases(sims_to_include))){
existing_exp_details <- filter_sims(which_object = existing_exp_details,
which_sims = sims_to_include,
include_or_omit = "include")
# existing_exp_details should now only have the sims they requested.
# Noting if any sims are missing.
MissingSims <- setdiff(sims_to_include,
existing_exp_details$MainDetails$File)
if(length(MissingSims) > 0){
warning(paste0("The following simulation files were not found in the ReleaseProfiles data for existing_exp_details:\n",
str_c(MissingSims, collapse = "\n"), "They will be ignored.\n"),
call. = FALSE)
}
} else {
sims_to_include <- unique(existing_exp_details$ReleaseProfiles$File)
}
if(all(is.na(compoundsToExtract))){
compoundsToExtract <- AllCompounds$CompoundID
}
# Checking for bad inputs on compounds
BadCmpd <- tolower(compoundsToExtract)[
which(tolower(compoundsToExtract) %in% AllCompounds$CompoundID == FALSE)]
GoodCmpd <- intersect(AllCompounds$CompoundID,
tolower(compoundsToExtract))
if(length(BadCmpd) > 0){
if(length(GoodCmpd) == 0){
stop(wrapn(paste0("None of the compounds you entered are among the possible options for compoundsToExtract: ",
str_comma(paste0("'", BadCmpd, "'")),
". Please check your inputs and try again.")),
call. = FALSE)
} else {
warning(wrapn(paste0("The following compounds are not among the possible options for compoundsToExtract: ",
str_comma(paste0("'", BadCmpd, "'")),
". They will be ignored.")),
call. = FALSE)
}
}
compoundsToExtract <- GoodCmpd
# Main body of function -------------------------------------------------
Release <- list()
for(ff in sims_to_include){
Release[[ff]] <- list()
Deets <- filter_sims(existing_exp_details,
which_sims = ff,
include_or_omit = "include")
for(cmpd in compoundsToExtract){
# Checking on whether compound was included in sim
if(as.logical(is.na(Deets$MainDetails[
AllCompounds$DetailNames[AllCompounds$CompoundID == cmpd]]))){
next
}
Suffix <- AllCompounds$Suffix[AllCompounds$CompoundID == cmpd]
# Different input data depending on the CR/MR input
if(complete.cases(Deets$MainDetails[[paste0("CR_MR_Input", Suffix)]]) &&
Deets$MainDetails[[paste0("CR_MR_Input", Suffix)]] ==
"Weibull"){
Release[[ff]][[cmpd]] <-
data.frame(CompoundID = cmpd,
Time = seq(from = 0,
to = Deets$MainDetails$SimDuration,
length.out = 500))
suppressWarnings(
Release[[ff]][[cmpd]]$Release_mean <-
pweibull(q = Release[[ff]][[cmpd]]$Time,
scale = Deets$MainDetails[[paste0("ReleaseProfile_alpha",
Suffix)]],
shape = Deets$MainDetails[[paste0("ReleaseProfile_beta",
Suffix)]]) *
Deets$MainDetails[[paste0("ReleaseProfile_Fmax", Suffix)]]
)
# I'm not clear on how to calculate the variation surrounding a
# weibull function, and this is giving me errors sometimes. Not
# showing anything but mean for Weibull release functions.
Release[[ff]][[cmpd]] <- Release[[ff]][[cmpd]] %>%
mutate(ReleaseUpper = Release_mean,
ReleaseLower = Release_mean)
# suppressWarnings(
# Release[[ff]][[cmpd]]$ReleaseUpper <-
# pweibull(q = Release[[ff]][[cmpd]]$Time,
#
# scale = Deets$MainDetails[[paste0("ReleaseProfile_alpha",
# Suffix)]] +
# Deets$MainDetails[[paste0("ReleaseProfile_alpha",
# Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_alpha_CV",
# Suffix)]],
#
# shape = Deets$MainDetails[[paste0("ReleaseProfile_beta",
# Suffix)]] +
# Deets$MainDetails[[paste0("ReleaseProfile_beta",
# Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_beta_CV",
# Suffix)]]) *
# (Deets$MainDetails[[paste0("ReleaseProfile_Fmax", Suffix)]] +
# Deets$MainDetails[[paste0("ReleaseProfile_Fmax", Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_Fmax_CV", Suffix)]])
# )
#
# suppressWarnings(
# Release[[ff]][[cmpd]]$ReleaseLower <-
# pweibull(q = Release[[ff]][[cmpd]]$Time,
#
# scale = Deets$MainDetails[[paste0("ReleaseProfile_alpha",
# Suffix)]] -
# Deets$MainDetails[[paste0("ReleaseProfile_alpha",
# Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_alpha_CV",
# Suffix)]],
#
# shape = Deets$MainDetails[[paste0("ReleaseProfile_beta",
# Suffix)]] -
# Deets$MainDetails[[paste0("ReleaseProfile_beta",
# Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_beta_CV",
# Suffix)]]) *
# (Deets$MainDetails[[paste0("ReleaseProfile_Fmax", Suffix)]] -
# Deets$MainDetails[[paste0("ReleaseProfile_Fmax", Suffix)]] *
# Deets$MainDetails[[paste0("ReleaseProfile_Fmax_CV", Suffix)]])
# )
Release[[ff]][[cmpd]] <- Release[[ff]][[cmpd]] %>%
mutate(Release_mean = Release_mean / 100,
ReleaseUpper = ReleaseUpper / 100,
ReleaseLower = ReleaseLower / 100,
ReleaseSD = NA, # FIXME - return to this later. This isn't going to have conventional SD, so I want to use ReleaseUpper and ReleaseLower instead.
Tissue_subtype = NA,
Simulated = TRUE,
# placeholders only
Inhibitor = "none",
Trial = "mean",
Tissue = "plasma",
Conc_units = "ng/mL",
Time_units = "hours",
DoseNum = 1)
} else {
if(nrow(Deets$ReleaseProfiles %>% filter(CompoundID == cmpd)) == 0){next}
Release[[ff]][[cmpd]] <- Deets$ReleaseProfiles %>%
filter(CompoundID == cmpd) %>%
mutate(Release_mean = Release_mean / 100,
ReleaseUpper = Release_mean + Release_mean * Release_CV,
ReleaseLower = Release_mean - Release_mean * Release_CV,
ReleaseSD = Release_mean * Release_CV,
Tissue_subtype = NA,
Simulated = TRUE,
# placeholders only
Inhibitor = "none",
Trial = "mean",
Tissue = "plasma",
Conc_units = "ng/mL",
Time_units = "hours",
DoseNum = 1)
}
}
Release[[ff]] <- bind_rows(Release[[ff]])
}
Release <- bind_rows(Release)
# Adding compounds names
suppressMessages(
MyCompounds <- existing_exp_details$MainDetails %>%
select(any_of(c("File", "Substrate", "PrimaryMetabolite1",
"PrimaryMetabolite2", "SecondaryMetabolite",
"Inhibitor1", "Inhibitor1Metabolite",
"Inhibitor2"))) %>%
pivot_longer(cols = -File,
names_to = "DetailNames",
values_to = "Compound") %>%
left_join(AllCompounds) %>%
select(File, CompoundID, Compound) %>%
filter(complete.cases(Compound))
)
suppressMessages(
Release <- Release %>% left_join(MyCompounds)
)
# ggplot(Release, aes(x = Time, y = Release_mean,
# ymax = ReleaseUpper, ymin = ReleaseLower)) +
# geom_point() + geom_line() +
# geom_ribbon(alpha = 0.5) +
# scale_x_time() +
# theme_consultancy()
facet1_column <- rlang::enquo(facet1_column)
facet2_column <- rlang::enquo(facet2_column)
colorBy_column <- rlang::enquo(colorBy_column)
linetype_column <- rlang::enquo(linetype_column)
# Including hacks to make this work
ct_plot_overlay(
ct_dataframe = Release,
figure_type = figure_type,
# NSE trouble: not enquo alone, not quo, not
# substitute, but enquo plus !! here
colorBy_column = !!colorBy_column,
linetype_column = !!linetype_column,
facet1_column = !!facet1_column,
facet2_column = !!facet2_column,
obs_to_sim_assignment = NA,
mean_type = "arithmetic",
linear_or_log = linear_or_log,
color_labels = color_labels,
legend_label_color = legend_label_color,
color_set = color_set,
include_errorbars = include_errorbars,
errorbar_width = errorbar_width,
linetype_labels = linetype_labels,
linetypes = linetypes,
line_width = line_width,
line_transparency = line_transparency,
legend_label_linetype = legend_label_linetype,
facet_ncol = facet_ncol,
facet_nrow = facet_nrow,
floating_facet_scale = floating_facet_scale,
facet_spacing = facet_spacing,
time_range = time_range,
x_axis_interval = x_axis_interval,
x_axis_label = x_axis_label,
pad_x_axis = pad_x_axis,
pad_y_axis = pad_y_axis,
y_axis_limits_lin = y_axis_limits_lin,
y_axis_limits_log = y_axis_limits_log,
y_axis_interval = y_axis_interval,
y_axis_label = y_axis_label,
hline_position = hline_position,
hline_style = hline_style,
vline_position = vline_position,
vline_style = vline_style,
graph_labels = graph_labels,
graph_title = graph_title,
graph_title_size = graph_title_size,
legend_position = legend_position,
prettify_compound_names = prettify_compound_names,
qc_graph = FALSE,
existing_exp_details = existing_exp_details,
save_graph = save_graph,
fig_height = fig_height,
fig_width = fig_width)
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.