stat_reduce {ggbio} | R Documentation |
Reduce GRanges
, IRanges
or TranscriptDb
object.
## S4 method for signature 'GRanges' stat_reduce(data, ..., xlab, ylab, main, drop.empty.ranges = FALSE, min.gapwidth = 1L, facets = NULL, geom = NULL) ## S4 method for signature 'IRanges' stat_reduce(data, ..., xlab, ylab, main, drop.empty.ranges = FALSE, min.gapwidth = 1L, with.inframe.attrib=FALSE, facets = NULL, geom = NULL) ## S4 method for signature 'TranscriptDb' stat_reduce(data, ...)
data |
|
... |
passed to aesthetics mapping. |
xlab |
x label. |
ylab |
y label. |
main |
title. |
drop.empty.ranges |
pass to |
min.gapwidth |
pass to |
with.inframe.attrib |
pass to |
facets |
pass to |
geom |
geometric type. |
a ggplot object.
Tengfei Yin
reduce
.
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"])
## Aggregating TranscriptDb...
## Parsing exons...
## Parsing cds...
## Parsing transcripts...
## Aggregating...
## Done
## Constructing graphics...