Workflow input from a GitHub release — tar_input

Targets for workflow input for mzML data files and sample information stored in a GitHub release using the piggyback R package.

Usage

tar_input_piggyback(
  name,
  tag,
  file = NULL,
  dest = paste0("data/", tag),
  sample_info_file = "runinfo.csv",
  ext = ".mzML.gz",
  repo = guess_repo(),
  overwrite = TRUE,
  ignore = "manifest.json",
  use_timestamps = TRUE,
  show_progress = TRUE,
  .token = gh::gh_token()
)

Arguments

name: Symbol. The name for the collection of targets. This serves as a prefix for target names.
tag: tag for the GitHub release to which this data should be attached.
file: name or vector of names of files to be downloaded. If NULL, all assets attached to the release will be downloaded.
dest: The directory destination of the downloaded release data.
sample_info_file: The name of the file included in the release that contains the sample information.
ext: The file extension of the converted (mzML) data files.
repo: Repository name in format "owner/repo". Defaults to guess_repo().
overwrite: Should any local files of the same name be overwritten? default TRUE.
ignore: a list of files to ignore (if downloading "all" because file=NULL).
use_timestamps: DEPRECATED.
show_progress: logical, show a progress bar be shown for uploading? Defaults to [interactive()] - can also set globally with options("piggyback.verbose")
.token: GitHub authentication token, see [gh::gh_token()]

Value

A list of target objects specifically for analysis pipeline input data retrieval using piggyback.

Examples

if (FALSE) {
## Example piggyback input
targets::tar_dir({
    targets::tar_script({
        library(hrmtargets)
        list(
            tar_input_piggyback(example,
                                'FIE-HRMS_BdistachyonTechnical',
                                repo = 'jasenfinch/metaboData')
        )
    })
    targets::tar_make()
    targets::tar_read(example_sample_information)
})
}