stat_coverage {ggbio} | R Documentation |
Calculate coverage.
# for GRanges ## S4 method for signature 'GRanges' stat_coverage(data, ..., xlim, xlab, ylab, main, facets = NULL, geom = NULL) # for GRangesList ## S4 method for signature 'GRangesList' stat_coverage(data, ..., xlim, xlab, ylab, main, facets = NULL, geom = NULL) # for Bamfile ## S4 method for signature 'BamFile' stat_coverage(data, ..., maxBinSize = 2^14, xlim, which, xlab, ylab, main, facets = NULL, geom = NULL, method = c("estimate", "raw"), space.skip = 0.1, coord = c("linear", "genome"))
data |
A |
... |
Extra parameters such as aes() passed to |
xlim |
Limits for x. |
xlab |
Label for x |
ylab |
Label for y |
main |
Title for plot. |
facets |
Faceting formula to use. |
geom |
The geometric object to use display the data. |
maxBinSize |
maxBinSize. |
method |
'estimate' for parsing estimated coverage(fast), 'raw' is slow and parse the accurate coverage. |
which |
|
space.skip |
used for coordinate genome, skip between chromosomes. |
coord |
coordinate system. |
A 'Layer'.
Tengfei Yin
library(ggbio)
## ======================================================================
## simmulated GRanges
## ======================================================================
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_coverage()
ggplot() + stat_coverage(gr)
ggplot(gr) + stat_coverage(geom = "point")
ggplot(gr) + stat_coverage(geom = "area")
ggplot(gr) + stat_coverage(aes(y = ..coverage..), geom = "histogram")
ggplot(gr) + stat_coverage(aes(y = ..coverage..)) + geom_point()
## for bam file
## TBD