stat_bin {ggbio} | 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")