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#' Summary of maxR object
#'
#' @param object Object of \code{"maxR"} class
#' @param ... Further arguments
#' @export
summary.maxR <- function(object, ...) {
ans <- list()
ans$call <- object$Call
ans$points <- outsidePoints(object$Ymean)
ans$totals <- data.frame("Call" = object$Call,
"Syn" = sum(object$Ymean$call == "Syn"),
"Ant" = sum(object$Ymean$call == "Ant"),
"Total" = nrow(object$Ymean))
class(ans) <- append("summary.maxR", class(ans))
ans
}
#' Print summary of maxR object
#'
#' @param x Summary of \code{"maxR"} object
#' @inheritParams summary.maxR
#' @export
print.summary.maxR <- function(x, ...) {
if (x$call != "None") {
x$points$`p-value` <- ifelse(x$points$`p-value` < 2e-16, "<2e-16",
round(x$points$`p-value`, 5))
cat("\nEvidence for effects in data: ", x$call, "\n", sep="")
cat("Points with significant deviations from the null: \n")
print(x$points)
rownames(x$totals) <- ""
cat("\nOverall maxR summary:\n")
print(x$totals)
} else {
cat("MaxR test did not detect any deviations from the null.\n")
}
}
#' Plot of maxR object
#'
#' @param x Output of \code{\link{maxR}}. This can also be \code{"maxR"}
#' element in the output of \code{\link{fitSurface}}.
#' @param plevels Probability levels used to generate a color scale
#' @param cutoff Probability cutoff to use for range of colors
#' @param maxshow Forced value for range of colors
#' @param ... Further arguments that are passed to \code{\link{format}} function
#' for formatting of axis labels
#' @inheritParams plotResponseSurface
#' @inheritParams contour.ResponseSurface
#' @inheritParams graphics::title
#' @importFrom graphics axis filled.contour points title
#' @importFrom grDevices extendrange rgb
#' @export
plot.maxR <- function(x,
main = "Contour plot for maxR",
xlab = "Dose (Compound 1)", ylab = "Dose (Compound 2)",
colorPalette = c("blue", "white", "red"),
logScale = TRUE, zTransform = function(z) { z },
plevels = c(0.7, 0.8, 0.9, 0.95, 0.99, 0.999),
cutoff = max(plevels), maxshow = NULL, reverse.x = FALSE, reverse.y = FALSE, swapAxes = FALSE, ...) {
uniqueDoses <- with(x$Ymean,
list("d1" = sort(unique(d1)),
"d2" = sort(unique(d2))))
doseGrid <- expand.grid(uniqueDoses)
log10T <- function(z) log10(z + 0.5 * min(z[z != 0]))
transformF <- if (logScale) log10T else function(z) z
maxRvalues <- x$Ymean$R
maxRvalues <- maxRvalues[match(with(doseGrid, paste(d1, d2)),
with(x$Ymean, paste(d1, d2)))]
maxRvalues[is.na(maxRvalues)] <- 0
if (is.null(maxshow)) {
## We show all values above cutoff in the same color
maxshow <- quantile(attr(x$Ymean, "distr"), cutoff)
if (is.null(maxshow)) {
maxshow <- 3.5
warning("No `maxshow` parameter specified, so 3.5 is used.")
}
}
origMaxRvalues <- maxRvalues # Keep unchanged for point sizes
maxRvalues[maxRvalues > maxshow] <- maxshow
maxRvalues[maxRvalues < -maxshow] <- -maxshow
## Levels to show on color-scale
zlevels <- sort(quantile(attr(x$Ymean, "distr"),
c(plevels[plevels < cutoff], cutoff)) %o% c(-1,1))
if(swapAxes){
if(reverse.x) xlim <- rev(extendrange(transformF(uniqueDoses$d2))) else xlim <- extendrange(transformF(uniqueDoses$d2))
if(reverse.y) ylim <- rev(extendrange(transformF(uniqueDoses$d1))) else ylim <- extendrange(transformF(uniqueDoses$d1))
filled.contour(
x = transformF(uniqueDoses$d2),
y = transformF(uniqueDoses$d1),
z = t(matrix(maxRvalues, sapply(uniqueDoses, length))),
levels = zlevels,
color.palette = colorRampPalette(colorPalette, space = "rgb"),
plot.axes = {
axis(1, at = transformF(uniqueDoses$d2),
labels = format(uniqueDoses$d2, ...), cex.axis = 0.8)
axis(2, at = transformF(uniqueDoses$d1),
labels = format(uniqueDoses$d1, ...), cex.axis = 0.8)
points(expand.grid(x = transformF(uniqueDoses$d2),
y = transformF(uniqueDoses$d1)),
pch = 20, col = rgb(0, 0, 0, 0.3),
## Size proportional to maxR statistic
cex = t(matrix(abs(origMaxRvalues)/2,
sapply(uniqueDoses, length))))
},
key.axes = {
axis(4, at = c(0, zlevels), tck = -0.1,
mgp = c(3, 0.3, 0), cex.axis = 0.7,
labels = c(
paste0("\u2191",
if (colorPalette[1] %in% c("blue", "white")) "Antagonism" else "Synergy",
"\n\n \n\n",
"\u2193",
if (colorPalette[1] %in% c("blue", "white")) "Synergy" else "Antagonism"),
paste0("\u2264", 1 - cutoff),
1 - rev(plevels[plevels < cutoff]),
1 - plevels[plevels < cutoff],
paste0("\u2264", 1 - cutoff))
)
},
key.title = title(main = "p-values", line = 1, cex.main = 1),
xlim = xlim,
ylim = ylim,
zlim = maxshow*c(-1, 1),
main = main,
xlab = ylab, ylab = xlab,
bty = "n"
)
} else {
if(reverse.x) xlim <- rev(extendrange(transformF(uniqueDoses$d1))) else xlim <- extendrange(transformF(uniqueDoses$d1))
if(reverse.y) ylim <- rev(extendrange(transformF(uniqueDoses$d2))) else ylim <- extendrange(transformF(uniqueDoses$d2))
filled.contour(
x = transformF(uniqueDoses$d1),
y = transformF(uniqueDoses$d2),
z = matrix(maxRvalues, sapply(uniqueDoses, length)),
levels = zlevels,
color.palette = colorRampPalette(colorPalette, space = "rgb"),
plot.axes = {
axis(1, at = transformF(uniqueDoses$d1),
labels = format(uniqueDoses$d1, ...), cex.axis = 0.8)
axis(2, at = transformF(uniqueDoses$d2),
labels = format(uniqueDoses$d2, ...), cex.axis = 0.8)
points(expand.grid(x = transformF(uniqueDoses$d1),
y = transformF(uniqueDoses$d2)),
pch = 20, col = rgb(0, 0, 0, 0.3),
## Size proportional to maxR statistic
cex = matrix(abs(origMaxRvalues)/2,
sapply(uniqueDoses, length)))
},
key.axes = {
axis(4, at = c(0, zlevels), tck = -0.1,
mgp = c(3, 0.3, 0), cex.axis = 0.7,
labels = c(
paste0("\u2191",
if (colorPalette[1] %in% c("blue", "white")) "Antagonism" else "Synergy",
"\n\n \n\n",
"\u2193",
if (colorPalette[1] %in% c("blue", "white")) "Synergy" else "Antagonism"),
paste0("\u2264", 1 - cutoff),
1 - rev(plevels[plevels < cutoff]),
1 - plevels[plevels < cutoff],
paste0("\u2264", 1 - cutoff))
)
},
key.title = title(main = "p-values", line = 1, cex.main = 1),
xlim = xlim,
ylim = ylim,
zlim = maxshow*c(-1, 1),
main = main,
xlab = xlab, ylab = ylab,
bty = "n"
)
}
}
#' List non-additive points
#'
#' List all points with corresponding p-values declared non-additive by the
#' maxR statistical test.
#'
#' @param maxR maxR statistics table returned by \code{Ymean} component from the
#' output of \code{\link{maxR}} function. This can also be \code{"maxR"}
#' element in the output of \code{\link{fitSurface}} function.
#' @param B Iterations to use for the distribution of the maxR statistic. This
#' is only used if \code{Ymean} dataframe does not have a \code{"distr"} attribute
#' attached as is normally done when using \code{\link{fitSurface}} or \code{\link{maxR}}
#' function.
#' @return Returns a dataframe listing only dose combinations that exhibit
#' significant deviations from the expected response surface.
#' @export
#' @examples
#' \donttest{
#' data <- subset(directAntivirals, experiment == 2)
#' ## Data must contain d1, d2 and effect columns
#' fitResult <- fitMarginals(data)
#' surf <- fitSurface(data, fitResult, statistic = "maxR")
#' outsidePoints(surf$maxR$Ymean)
#' }
outsidePoints <- function(maxR, B = 10000) {
if (is.null(attr(maxR, "distr"))) {
n1 <- nrow(maxR)
df0 <- attr(maxR, "df0")
stopifnot(length(n1) == 1)
stopifnot(length(df0) == 1)
sim1 <- abs(matrix(rt(B*n1, df = df0), ncol = n1, byrow = TRUE))
distr <- apply(sim1, 1, max) #q1 <- quantile(apply(sim1, 1, max), cutoff)
f <- ecdf(distr)
} else f <- attr(maxR, "distr")
resDF <- maxR[maxR$sign, ]
resDF$`p-value` <- 1-f(resDF$absR)
if (nrow(resDF) > 0) resDF[, c(1:2, 4, 8, 7)] else NULL
}
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