get_ssRleCov: Get Rle coverage from a bedgraph file for a sample

In haibol2016/InPAS: Identify Novel Alternative PolyAdenylation Sites (PAS) from RNA-seq data

Get Rle coverage from a bedgraph file for a sample

Description

Get RLe coverage from a bedgraph file for a sample

Usage

get_ssRleCov(
  bedgraph,
  tag,
  genome = getInPASGenome(),
  sqlite_db,
  future.chunk.size = NULL,
  outdir = getInPASOutputDirectory(),
  chr2exclude = getChr2Exclude()
)

Arguments

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 BSgenome::forgeBSgenomeDataPkg().
sqlite_db	A path to the SQLite database for InPAS, i.e. the output of setup_sqlitedb().
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. chrM and alternative scaffolds representing different haplotypes should be excluded.

Value

A data frame, as described below.

tag

the sample tag

chr

chromosome name

coverage_file

path to Rle coverage files for each chromosome per sample tag

Author(s)

Jianhong Ou, Haibo Liu

Examples

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)
}

haibol2016/InPAS documentation built on March 30, 2022, 10:30 a.m.