stat_bin | R Documentation |
Binning method especially for Rle
and RleList
, for
data.frame
it's just calling ggplot2::stat_bin
.
## S4 method for signature 'ANY'
stat_bin(data, ...)
## S4 method for signature 'Rle'
stat_bin(data, ..., binwidth, nbin = 30,
xlab, ylab, main, geom = c("bar", "heatmap"),
type = c("viewSums","viewMins",
"viewMaxs", "viewMeans"))
## S4 method for signature 'RleList'
stat_bin(data, ..., binwidth, nbin = 30,
xlab, ylab, main,
indName = "sample",
geom = c("bar", "heatmap"),
type = c("viewSums","viewMins",
"viewMaxs", "viewMeans"))
data |
Typically a |
... |
arguments passed to aesthetics mapping. |
binwidth |
width of the bins. |
nbin |
number of bins. |
xlab |
x label. |
ylab |
y label. |
main |
title. |
indName |
when faceted by a |
geom |
geometric types. |
type |
statistical summary method used within bins, shown as bar height or heatmap colors. |
a ggplot object.
Tengfei Yin
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() + stat_bin(xRle)
ggplot(xRle) + stat_bin()
ggplot(xRle) + stat_bin(nbin = 100)
ggplot(xRle) + stat_bin(binwidth = 200)
p1 <- ggplot(xRle) + stat_bin(type = "viewMeans")
p2 <- ggplot(xRle) + stat_bin(type = "viewSums")
## y scale are different.
tracks(viewMeans = p1, viewSums = p2)
ggplot(xRle) + stat_bin(geom = "heatmap")
ggplot(xRle) + stat_bin(nbin = 100, geom = "heatmap")
ggplot(xRle) + stat_bin(binwidth = 200, geom = "heatmap")
## for RleList
ggplot(xRleList) + stat_bin()
ggplot(xRleList) + stat_bin(nbin = 100)
ggplot(xRleList) + stat_bin(binwidth = 200)
p1 <- ggplot(xRleList) + stat_bin(type = "viewMeans")
p2 <- ggplot(xRleList) + stat_bin(type = "viewSums")
## y scale are different.
tracks(viewMeans = p1, viewSums = p2)
ggplot(xRleList) + stat_bin(geom = "heatmap")
ggplot(xRleList) + stat_bin(nbin = 100, geom = "heatmap")
ggplot(xRleList) + stat_bin(binwidth = 200, geom = "heatmap")
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