ggbio (version 1.20.0)

stat_reduce: Reduce an object.

Description

Reduce GRanges, IRanges or TxDb object.

Usage

"stat_reduce"(data, ..., xlab, ylab, main, drop.empty.ranges = FALSE, min.gapwidth = 1L, facets = NULL, geom = NULL)
"stat_reduce"(data, ..., xlab, ylab, main, drop.empty.ranges = FALSE, min.gapwidth = 1L, with.inframe.attrib=FALSE, facets = NULL, geom = NULL)
"stat_reduce"(data, ...)

Arguments

data
GRanges, IRanges or TxDb object.
...
passed to aesthetics mapping.
xlab
x label.
ylab
y label.
main
title.
drop.empty.ranges
pass to reduce function.
min.gapwidth
pass to reduce function.
with.inframe.attrib
pass to reduce function.
facets
pass to reduce function.
geom
geometric type.

Value

a ggplot object.

See Also

reduce.

Examples

Run this code
set.seed(1)
N <- 1000
library(GenomicRanges)

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))

ggplot(gr) + stat_reduce()
autoplot(gr, stat = "reduce")
strand(gr) <- "*"
ggplot(gr) + stat_reduce()

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
data(genesymbol, package = "biovizBase")
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
## made a track comparing full/reduce stat.
ggplot(txdb) + stat_reduce(which = genesymbol["RBM17"])

Run the code above in your browser using DataCamp Workspace