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

In ggbio: Visualization tools for genomic data

Description

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

Usage

## S4 method for signature '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"))

## S4 method for signature '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.

Author(s)

Tengfei Yin

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)

ggbio documentation built on Nov. 8, 2020, 5:04 p.m.