getData | R Documentation |
Evaluation of data recipes to generate curated dataset of interest.
getData(
rcp,
outdir,
prefix = NULL,
notes = c(),
conda = FALSE,
BPPARAM = NULL,
...
)
rcp |
the data recipe in |
outdir |
Character string specifying the directory to store the output files. Will automatically create if not exist or provided. |
prefix |
Character string specifying the file name of the annotation files (.yml, .cwl, .sh, .md5). |
notes |
User assigned notes/keywords to annotate the data and
be used for keywords matching in |
conda |
Whether to use conda to install required software when evaluating the data recipe as a CWL workflow. Default is FALSE. |
BPPARAM |
The options for |
... |
Arguments to be passed into |
The data files and 4 meta files: .cwl
: The cwl script
that was internally run to get the data; .yml
: the input
parameter values for the data recipe and user specified data
annotation notes, versions etc; .sh
: The script for data
processing; .md
: checksum file to verify the integrity of
generated data files.
## Not run:
library(Rcwl)
outdir <- file.path(tempdir(), "SharedData")
## Example 1
echo_out <- recipeLoad("echo_out")
Rcwl::inputs(echo_out)
echo_out$input <- "Hello World!"
echo_out$outfile <- "outfile"
res <- getData(echo_out,
outdir = outdir,
notes = c("echo", "hello", "world", "txt"),
showLog = TRUE)
# Example 2
ensembl_liftover <- recipeLoad("ensembl_liftover")
Rcwl::inputs(ensembl_liftover)
ensembl_liftover$species <- "human"
ensembl_liftover$from <- "GRCh37"
ensembl_liftover$to <- "GRCh38"
res <- getData(ensembl_liftover,
outdir = outdir,
notes = c("ensembl", "liftover", "human", "GRCh37", "GRCh38"),
showLog = TRUE)
dir(outdir)
## End(Not run)
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