ggbio (version 1.20.0)

stat_slice: Slice Rle/RleList to view them as bar or heatmap.

Description

Slice Rle/RleList to different view by set lower or other parameters, then view summary for all those viewed region.

Usage

"stat_slice"(data, ..., xlab, ylab, main, na.rm = FALSE, geom = NULL, lower=-Inf, upper=Inf, includeLower=TRUE, includeUpper=TRUE, rangesOnly = FALSE, type = c("viewSums","viewMins", "viewMaxs", "viewMeans"))
"stat_slice"(data, ..., xlab, ylab, main, indName = "sample", na.rm = FALSE, geom = NULL, lower=-Inf, upper=Inf, includeLower=TRUE, includeUpper=TRUE, rangesOnly = FALSE, type = c("viewSums","viewMins", "viewMaxs", "viewMeans"))

Arguments

data
a data.frame or Rle or RleList object.
...
arguments passed to aesthetics mapping.
xlab
x label.
ylab
y label.
main
title.
indName
when faceted by a RleList, name used for labeling faceted factor. Default is 'sample'.
geom
geometric types.
type
statistical summary method used within bins, shown as bar height or heatmap colors.
na.rm
logical value, default FALSE, passed to function like viewMaxs for statistical summary computation.
lower
passed to slice.
upper
passed to slice.
includeLower
passed to slice.
includeUpper
passed to slice.
rangesOnly
passed to slice.

Value

a ggplot object.

See Also

slice

Examples

Run this code
library(IRanges)
lambda <- c(rep(0.001, 4500), seq(0.001, 10, length = 500), 
            seq(10, 0.001, length = 500))
xVector <- rpois(1e4, lambda)
xRle <- Rle(xVector)
xRleList <- RleList(xRle, 2L * xRle)

ggplot(xRle) + stat_slice(lower = 5)
ggplot(xRle) + stat_slice(lower = 5, geom = "bar")
ggplot(xRle) + stat_slice(lower = 5, geom = "heatmap")

p1 <- ggplot(xRle) + stat_slice(type = "viewMeans", lower = 5,
                            geom = "bar")
p2 <- ggplot(xRle) + stat_slice(type = "viewSums", lower = 5,
                            geom = "bar")
## y scale are different.
tracks(viewMeans = p1, viewSums = p2)

ggplot(xRleList) + stat_slice(lower = 5)
ggplot(xRleList) + stat_slice(lower = 5, geom = "bar")
ggplot(xRleList) + stat_slice(lower = 5, geom = "heatmap")

p1 <- ggplot(xRleList) + stat_slice(type = "viewMeans", lower = 5,
                            geom = "bar")
p2 <- ggplot(xRleList) + stat_slice(type = "viewSums", lower = 5,
                            geom = "bar")
## y scale are different.
tracks(viewMeans = p1, viewSums = p2)

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