View source: R/03.get_ssRleCov.R
get_ssRleCov | R Documentation |
Get RLe coverage from a bedgraph file for a sample
get_ssRleCov(
bedgraph,
tag,
genome = getInPASGenome(),
sqlite_db,
future.chunk.size = NULL,
outdir = getInPASOutputDirectory(),
chr2exclude = getChr2Exclude()
)
bedgraph |
A path to a bedGraph file |
tag |
A character(1) vector, a name tag used to label the bedgraph file. It must match the tag specified in the metadata file used to setup the SQLite database |
genome |
an object BSgenome::BSgenome. To make things easy, we
suggest users creating a BSgenome::BSgenome instance from the
reference genome used for read alignment. For details, see the
documentation of |
sqlite_db |
A path to the SQLite database for InPAS, i.e. the output of
|
future.chunk.size |
The average number of elements per future ("chunk"). If Inf, then all elements are processed in a single future. If NULL, then argument future.scheduling = 1 is used by default. Users can set future.chunk.size = total number of elements/number of cores set for the backend. See the future.apply package for details. You may adjust this number based based on the available computing resource: CPUs and RAM. This parameter affects the time for converting coverage from bedgraph to Rle. |
outdir |
A character(1) vector, a path with write permission for storing InPAS analysis results. If it doesn't exist, it will be created. |
chr2exclude |
A character vector, NA or NULL, specifying chromosomes or
scaffolds to be excluded for InPAS analysis. |
A data frame, as described below.
the sample tag
chromosome name
path to Rle coverage files for each chromosome per sample tag
Jianhong Ou, Haibo Liu
if (interactive()) {
library(BSgenome.Mmusculus.UCSC.mm10)
genome <- BSgenome.Mmusculus.UCSC.mm10
bedgraphs <- system.file("extdata", c(
"Baf3.extract.bedgraph",
"UM15.extract.bedgraph"
),
package = "InPAS"
)
tags <- c("Baf3", "UM15")
metadata <- data.frame(
tag = tags,
condition = c("Baf3", "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()
coverage_info <- get_ssRleCov(
bedgraph = bedgraphs[1],
tag = tags[1],
genome = genome,
sqlite_db = sqlite_db,
outdir = outdir,
chr2exclude = "chrM"
)
# check read coverage depth
db_connect <- dbConnect(drv = RSQLite::SQLite(), dbname = sqlite_db)
dbReadTable(db_connect, "metadata")
dbDisconnect(db_connect)
}
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