Nothing
qcscatterplot <- function(object, plotType, showOutliers)
{
data <- object@plotdata
data <- data[grepl(qcProbes[plotType], data$Type),]
data <- droplevels(data)
gp <- ggplot(data, aes_string(x="IntRed", y="IntGrn", colour = "ExtendedType"))
gp <- gp + geom_point()
gp <- gp + ggtitle(unique(data$Type))
gp <- gp + xlab(expression(paste(log[2], "Probe Intensity (Red)")))
gp <- gp + ylab(expression(paste(log[2], "Probe Intensity (Green)")))
if(exists("highlight", envir=globalenv()))
{
highlight <- get("highlight", envir=globalenv())
id <- as.character(data$Samples) == highlight
gp <- gp + geom_point(data = data[id,],
aes_string(x="IntRed", y="IntGrn"),
colour="black", size = 4, shape = 4)
}
if(showOutliers)
{
outliers <- getOutliers(as.character(data$Samples))
if(any(outliers))
gp <- gp + geom_point(data = data[outliers,],
aes_string(x="IntRed", y="IntGrn"),
colour="black", size = 3, shape = 8)
}
gp
}
qcsampleplot <- function(object, plotType, showOutliers)
{
data <- object@plotdata
d <- data[grepl(qcProbes[plotType], data$Type),]
dGrn <- d[,c(1:5, 7)]
dGrn[,"Channel"] <- "Grn"
dRed <- d[, c(1:6)]
dRed[,"Channel"] <- "Red"
colnames(dGrn)[6] <- colnames(dRed)[6] <- "Intensity"
data <- rbind(dGrn, dRed)
data$Samples <- as.character(data$Samples)
sampleNames <- data$Samples
##a la GenomeStudio when the number of samples less then 100
if(length(unique(sampleNames)) > 100)
data$Samples <- 1:nrow(data)
gp <- ggplot(data, aes_string(x="Samples", y="Intensity", colour = "ExtendedType"))
gp <- gp + geom_point()
gp <- gp + ggtitle(unique(data$Type))
gp <- gp + theme(axis.text.x = element_text(angle = 90, hjust = 1))
gp <- gp + facet_grid(.~Channel, scales="free")
gp <- gp + ylab(expression(paste(log[2], "Probe Intensity")))
gp <- gp + xlab("")
if(exists("highlight", envir=globalenv()))
{
highlight <- get("highlight", envir=globalenv())
id <- sampleNames == highlight
gp <- gp + geom_point(data = data[id,],
aes_string(x = "Samples", y = "Intensity"),
shape=4, colour="black", size = 4)
}
if(showOutliers)
{
outliers <- getOutliers(sampleNames)
if(any(outliers))
gp <- gp + geom_point(data = data[outliers,],
aes_string(x = "Samples", y = "Intensity"),
shape = 8, colour="black", size = 3)
}
gp
}
qcboxplot <- function(object, plotType, showOutliers)
{
data <- object@plotdata
d <- data[grepl(qcProbes[plotType], data$Type),]
dGrn <- d[,c(1:5, 7)]
dGrn[,"Channel"] <- "Grn"
dRed <- d[, c(1:6)]
dRed[,"Channel"] <- "Red"
colnames(dGrn)[6] <- colnames(dRed)[6] <- "Intensity"
data <- rbind(dGrn, dRed)
gp <- ggplot(data,
aes_string(x = "Channel", y = "Intensity", colour = "ExtendedType"))
gp <- gp + geom_boxplot()
gp <- gp + ggtitle(unique(data$Type))
gp <- gp + ylab(expression(paste(log[2], "Probe Intensity")))
if(exists("highlight", envir=globalenv()))
{
highlight <- get("highlight", envir=globalenv())
id <- as.character(data$Samples) == highlight
gp <- gp + geom_point(data = data[id,],
aes_string(x = "Channel", y = "Intensity"),
colour="black", size = 4.5, shape = 4)
}
if(showOutliers)
{
outliers <- getOutliers(as.character(data$Samples))
if(any(outliers))
gp <- gp + geom_point(data = data[outliers,],
aes_string(x = "Channel", y = "Intensity"),
colour="black", size = 3, shape = 8)
}
gp
}
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