ggbio (version 1.20.1)

geom_chevron: Chevron geoms for GRanges object

Description

Break normal intervals stroed in GRanges object and show them as chevron, useful for showing model or splice summary.

Usage

## S3 method for class 'GRanges':
geom_chevron(data, ..., xlab, ylab, main,
             offset = 0.1,
             facets = NULL,
             stat = c("stepping", "identity"),
             chevron.height.rescale = c(0.1, 0.8),
             group.selfish = TRUE)

Arguments

data
A GRanges object.
...
Extra parameters passed to autoplot function.
xlab
Label for x
ylab
Label for y
main
Title for plot.
offset
A nunmeric value or characters. If it's numeric value, indicate how much you want the chevron to wiggle, usually the rectangle for drawing GRanges is of height unit 1, so it's better between -0.5 and 0.5 to make it nice looking. Unless you specify offset as one of those columns, this will use height of the chevron to indicate the columns. Of course you could use size of the chevron to indicate the column variable easily, please see the examples.
facets
faceting formula to use.
stat
character vector specifying statistics to use. "stepping" with randomly assigned stepping levels as y varialbe. "identity" allow users to specify y value in aes.
chevron.height.rescale
A numeric vector of length 2. When the offset parameters is a character which is one of the data columns, this parameter rescale the offset.
group.selfish
Passed to addStepping, control whether to show each group as unique level or not. If set to FALSE, if two groups are not overlapped with each other, they will probably be layout in the same level to save space.

Value

  • A 'Layer'.

Details

To draw a normal GRanges as Chevron, we need to provide a special geom for this purpose. Chevron is popular in gene viewer or genomoe browser, when they try to show isoforms or gene model.geom_chevron, just like any other geom_* function in ggplot2, you can pass aes() to it to use height of chevron or width of chevron to show statistics summary.

Examples

Run this code
set.seed(1)
N <- 100
require(GenomicRanges)

## ======================================================================
##  simmulated GRanges
## ======================================================================
gr <- GRanges(seqnames = 
              sample(c("chr1", "chr2", "chr3"),
                     size = N, replace = TRUE),
              IRanges(
                      start = sample(1:300, size = N, replace = TRUE),
                      width = sample(70:75, size = N,replace = TRUE)),
              strand = sample(c("+", "-", "*"), size = N, 
                replace = TRUE),
              value = rnorm(N, 10, 3), score = rnorm(N, 100, 30),
              sample = sample(c("Normal", "Tumor"), 
                size = N, replace = TRUE),
              pair = sample(letters, size = N, 
                replace = TRUE))



## ======================================================================
##  default
##
##  ======================================================================
ggplot(gr) + geom_chevron()
## or
ggplot() + geom_chevron(gr)


## ======================================================================
##  facetting and aesthetics
## ======================================================================
ggplot(gr) + geom_chevron(facets = sample ~ seqnames, aes(color = strand))


## ======================================================================
##  stat:identity
## ======================================================================
ggplot(gr) + geom_chevron(stat = "identity", aes(y = value))


## ======================================================================
##  stat:stepping
## ======================================================================
ggplot(gr) + geom_chevron(stat = "stepping", aes(group = pair))


## ======================================================================
##  group.selfish controls when 
## ======================================================================
ggplot(gr) + geom_chevron(stat = "stepping", aes(group = pair), group.selfish = FALSE,
                        xlab = "xlab", ylab = "ylab", main = "main")

p <- qplot(x = mpg, y = cyl, data = mtcars)

## ======================================================================
##  offset
## ======================================================================
gr2 <- GRanges("chr1", IRanges(c(1, 10, 20), width = 5))
gr2.p <- gaps(gr2)
## resize to connect them
gr2.p <- resize(gr2.p, fix = "center", width = width(gr2.p)+2)

ggplot(gr2) + geom_rect() + geom_chevron(gr2.p)


## notice the rectangle height is 0.8
## offset = 0 just like a line
ggplot(gr2) + geom_rect() + geom_chevron(gr2.p, offset = 0)


## equal height
ggplot(gr2) + geom_rect() + geom_chevron(gr2.p, offset = 0.4)


## ======================================================================
##  chevron.height
## ======================================================================
values(gr2.p)$score <- c(100, 200)
ggplot(gr2) + geom_rect() + geom_chevron(gr2.p, offset = "score")
## chevron.height
ggplot(gr2) + geom_rect() + geom_chevron(gr2.p, offset = "score",
                                         chevron.height.rescale = c(0.4, 10))

Run the code above in your browser using DataCamp Workspace