Retrieve the design of a dataset

get_dataset_design(
  dataset,
  raw = getOption("gemma.raw", FALSE),
  memoised = getOption("gemma.memoised", FALSE),
  file = getOption("gemma.file", NA_character_),
  overwrite = getOption("gemma.overwrite", FALSE)
)

Arguments

dataset: A numerical dataset identifier or a dataset short name
raw: TRUE to receive results as-is from Gemma, or FALSE to enable parsing. Raw results usually contain additional fields and flags that are omitted in the parsed results.
memoised: Whether or not to save to cache for future calls with the same inputs and use the result saved in cache if a result is already saved. Doing options(gemma.memoised = TRUE) will ensure that the cache is always used. Use forget_gemma_memoised to clear the cache.
file: The name of a file to save the results to, or NULL to not write results to a file. If raw == TRUE, the output will be the raw endpoint from the API, likely a JSON or a gzip file. Otherwise, it will be a RDS file.
overwrite: Whether or not to overwrite if a file exists at the specified filename.

Value

A data table of the design matrix for the queried dataset. A 404 error if the given identifier does not map to any object

Examples

head(get_dataset_design("GSE2018"))
#>                          batch
#> BAL_47c_A0B1 Batch_06_02_07_24
#> BAL_47b_A0B1 Batch_07_02_10_03
#> BAL_47a_A0B0 Batch_08_02_10_15
#> BAL_46_A2B0  Batch_01_02_01_31
#> BAL_45b_A2B0 Batch_03_02_05_22
#> BAL_45a_A1B0 Batch_06_02_07_24
#>                                                         diseaseState
#> BAL_47c_A0B1                                  reference_subject_role
#> BAL_47b_A0B1                                  reference_subject_role
#> BAL_47a_A0B0                                  reference_subject_role
#> BAL_46_A2B0  disease_related_to_solid_organ_transplantation_|_lung_|
#> BAL_45b_A2B0 disease_related_to_solid_organ_transplantation_|_lung_|
#> BAL_45a_A1B0                                  reference_subject_role