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#' @title A function to visualise the sensitivity as a function of PDXn and PDXr
#'
#' @description This is an internal function. Please use cautiously if calling directly.
#' A visualisation of the sensitivity from the simulations
#'
#' @param data data frame with four columns which indicate the PDXn, PDXr, Biol_RR and the MissedCalls for a specified go-no go threshold
#'
#' @return a graphic visualisation
#'
#' @author Maria Luisa Guerriero, \email{maria.guerriero@@astrazeneca.com}
#' @author Natasha A. Karp, \email{natasha.karp@@astrazeneca.com}
#'
plotSensitivity <- function(data) {
ggplot(data=data, mapping=aes_string(x="PDXn", y="MissedCalls")) +
geom_point(size=4, mapping=aes(col=paste(data$Biol_RR, "%"))) +
geom_smooth(method="loess", se=FALSE,mapping=aes(col=paste(data$Biol_RR, "%"))) +
xlab("Number of PDX models") +
ylab("Missed calls (%)") +
scale_x_continuous(breaks = data$PDXn,
labels = data$PDXn) +
guides(colour=guide_legend("Biological\nresponse rate")) +
#ylim(0,100) +
theme(axis.text=element_text(size=16), axis.title=element_text(size=16,face="bold"), legend.title=element_text(size=16,face="bold"),
legend.title.align=0.5, strip.text = element_text(size=16, face="bold"), strip.text.y = element_text(angle = 0)) +
facet_grid(PDXr~., labeller = as_labeller(c(`1` = "Number of animals\nper PDX model\n\n\n1",`3` = "Number of animals\nper PDX model\n\n\n3",`5` = "Number of animals\nper PDX model\n\n\n5",`7` = "Number of animals\nper PDX model\n\n\n7")))
}
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