#' Draw scatter plots of posterior probabilities from both RIVER GAM in terms
#' of outlier status.
#'
#' \code{plotPosteriors} draws scatter plots of posterior probabilities from
#' both RIVER GAM (genomic annotation model) in terms of outlier
#' status.
#'
#' @param postprobs Output of \code{evaRIVER}, which provides test posterior
#' probabilities from both RIVER and GAM for all instances.
#' @param outliers Outlier status of examples
#'
#' @return A figure of posteriors from RIVER (y-axis) and GAM (x-axis) models
#' for ouliters and non-outliers separately
#'
#' @author Yungil Kim, \email{ipw012@@gmail.com}
#'
#' @examples
#' dataInput <- getData(filename=system.file("extdata", "simulation_RIVER.gz",
#' package = "RIVER"), ZscoreThrd=1.5)
#' postprobs <- appRIVER(dataInput)
#' plotPosteriors(postprobs, outliers=as.numeric(unlist(dataInput$Outlier))-1)
#'
#' @export
plotPosteriors <- function(postprobs, outliers) {
probFuncRv_Feat <- probFuncRv_FeatOut <- Outliers <- NULL
par(mar=c(6.1, 6.1, 4.1, 4.1))
dat <- data.frame(probFuncRv_Feat=postprobs$GAM_posterior,
probFuncRv_FeatOut=postprobs$RIVER_posterior,
outliers=as.factor(outliers))
ggplot(dat, aes_string(x="probFuncRv_Feat",
y="probFuncRv_FeatOut",
color="outliers")) +
geom_point(shape=1, size=4) +
geom_abline(intercept=0, slope=1, color="darkgray",
size=1, linetype=2) +
theme_bw() + xlab("P( FR | G)") + ylab("P( FR | G, E)") +
scale_color_manual(values=c("dodgerblue","mediumpurple"),
name="", breaks=c("0", "1"),
labels=c("Non-outlier", "Outlier")) +
theme(axis.title = element_text(size=18),
axis.text = element_text(size=14),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
legend.title = element_blank(),
legend.position = c(0.15,0.9),
legend.text = element_text(size=16),
legend.key = element_blank())
}
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