stat_bin {ggbio} | R Documentation

## Binning method

### Description

Binning method especially for `Rle` and `RleList`, for `data.frame` it's just calling `ggplot2::stat_bin`.

### Usage

    ## 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"))

### Arguments

`data` | Typically a `data.frame` or `Rle` or `RleList` object.
`...` | 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 `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.

### Value

a ggplot object.

### Author(s)

Tengfei Yin

### Examples

    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")

[Package ggbio version 1.36.0 Index]