ggbio (version 1.20.1)

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

## S3 method for class 'Rle':
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"))
## S3 method for class 'RleList':
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

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)