Nothing
##' @title Visualization of Raw gRNA Count Densities
##' @description This function plots the per-sample densities of raw gRNA read counts on the log10 scale. The curve colors are assigned based on a user-
##' specified sampleKey. This function is primarily useful to determine whether libraries are undersequenced (low mean raw gRNA counts),
##' contaminated (many low-abundance gRNAs present), or if PCR artifacts may be present (subset of extremely abundant guides, multiple gRNA distribution modes). In most
##' well-executed experiments the majority of gRNAs will form a tight distribution around some reasonably high average read count (hundreds of reads),
##' at least among the control samples. Excessively low raw count values can compromise normalization steps and subsequent estimation of gRNA levels, especially
##' in screens in which most gRNAs have minimal effects on cell viability.
##' @param eset An ExpressionSet object containing, at minimum, count data accessible by exprs() and some phenoData.
##' @param sampleKey A sample key, supplied as a (possibly ordered) factor linking the samples to experimental
##' variables. The \code{names} attribute should exactly match those present in \code{eset}, and the control set
##' is assumed to be the first \code{level}.
##' @param lib.size Optional named vector of library sizes (total reads within the library) to enable normalization
##' @return A density plot as specified on the default device.
##' @author Russell Bainer
##' @examples
##' data('es')
##'
##' #Build the sample key
##' library(Biobase)
##' sk <- relevel(as.factor(pData(es)$TREATMENT_NAME), "ControlReference")
##' names(sk) <- row.names(pData(es))
##'
##' ct.rawCountDensities(es, sk)
##' @export
ct.rawCountDensities <- function(eset, sampleKey = NULL, lib.size = NULL){
if(!methods::is(eset, "ExpressionSet")){stop(paste(deparse(substitute(eset)), "is not an ExpressionSet."))}
if (is.null(sampleKey)) {
sampleKey <- as.factor(colnames(eset))
names(sampleKey) <- sampleKey
} else {
ct.inputCheck(sampleKey, eset)
sampleKey <- sampleKey[order(sampleKey)]
}
counts <- exprs(eset)
if(!is.null(lib.size)){
stopifnot(setequal(names(lib.size), colnames(counts)), all(is.numeric(lib.size)))
counts <- t(t(counts)/(lib.size[colnames(counts)]/1000000))
message('Valid lib.sizes provided. Results will be in CPM.')
}
e.dat <- log10(counts + 1)
densities <- apply(e.dat, 2, density)
y <- c(0, max(unlist(lapply(densities, function(dens){max(dens$y)}))))
x <- c(0, max(ceiling(unlist(lapply(densities, function(dens){max(dens$x)})))));
plot(x[1], y[1],
xlim = x, ylim = y,
xlab = "gRNA Read Counts (Log10 Scale)",
ylab = "Density",
pch = NA,
main = "Raw gRNA Count Density",
xaxt = "n")
axis(1, at= 0:x[2], labels = 10^(0:x[2]))
#Set up colors for the factor
colors <- colorRampPalette(c("blue", "red"), alpha = TRUE)(length(levels(sampleKey)))
colors <- gsub("FF$", "99", colors, perl = TRUE)
invisible(lapply(seq_len(length(densities)),
function(x){lines(densities[[x]],
col = colors[as.numeric(sampleKey[colnames(e.dat)[x]])])}
)
)
legend("topright", legend = levels(sampleKey), fill = colors)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.