View source: R/26.get_usage4plot.R
get_usage4plot | R Documentation |
prepare coverage data and fitting data for plot
get_usage4plot(gr, proximalSites, sqlite_db, hugeData)
gr |
An object of GenomicRanges::GRanges |
proximalSites |
An integer(n) vector, specifying the coordinates of
proximal CP sites. Each of the proximal sites must match one entry in the
GRanges object, |
sqlite_db |
A path to the SQLite database for InPAS, i.e. the output of
|
hugeData |
A logical(1), indicating whether it is huge data |
An object of GenomicRanges::GRanges with metadata:
dat |
A data.frame, first column is the position, the other columns are Coverage and value |
offset |
offset from the start of 3' UTR |
Jianhong Ou, Haibo Liu
library(BSgenome.Mmusculus.UCSC.mm10)
library(TxDb.Mmusculus.UCSC.mm10.knownGene)
genome <- BSgenome.Mmusculus.UCSC.mm10
TxDb <- TxDb.Mmusculus.UCSC.mm10.knownGene
## load UTR3 annotation and convert it into a GRangesList
data(utr3.mm10)
utr3 <- split(utr3.mm10, seqnames(utr3.mm10), drop = TRUE)
bedgraphs <- system.file("extdata", c(
"Baf3.extract.bedgraph",
"UM15.extract.bedgraph"
),
package = "InPAS"
)
tags <- c("Baf3", "UM15")
metadata <- data.frame(
tag = tags,
condition = c("baf", "UM15"),
bedgraph_file = bedgraphs
)
outdir <- tempdir()
write.table(metadata,
file = file.path(outdir, "metadata.txt"),
sep = "\t", quote = FALSE, row.names = FALSE
)
sqlite_db <- setup_sqlitedb(
metadata = file.path(
outdir,
"metadata.txt"
),
outdir
)
addLockName(filename = tempfile())
coverage <- list()
for (i in seq_along(bedgraphs)) {
coverage[[tags[i]]] <- get_ssRleCov(
bedgraph = bedgraphs[i],
tag = tags[i],
genome = genome,
sqlite_db = sqlite_db,
outdir = outdir,
chr2exclude = "chrM"
)
}
data4CPsSearch <- setup_CPsSearch(sqlite_db,
genome,
chr.utr3 = utr3[["chr6"]],
seqname = "chr6",
background = "10K",
TxDb = TxDb,
hugeData = TRUE,
outdir = outdir
)
gr <- GRanges("chr6", IRanges(128846245, 128850081), strand = "-")
names(gr) <- "chr6:128846245-128850081"
data4plot <- get_usage4plot(gr,
proximalSites = 128849148,
sqlite_db,
hugeData = TRUE
)
plot_utr3Usage(
usage_data = data4plot,
vline_color = "purple",
vline_type = "dashed"
)
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