Downloads the MTBLS242 dataset from Gralka et al., 2015. DOI: doi:10.3945/ajcn.115.110536 .
download_MTBLS242(
dest_dir = "MTBLS242",
force = FALSE,
keep_only_CPMG_1r = TRUE,
keep_only_preop_and_3months = TRUE,
keep_only_complete_time_points = TRUE
)
Directory where the dataset should be saved
Logical. If TRUE
we do not re-download files if they exist. The function does not check whether cached versions were
downloaded with different keep_only_*
arguments, so please use force = TRUE
if you change the keep_only_*
settings.
If TRUE
, remove all other data beyond the CPMG real spectrum, which is enough for the tutorial
If TRUE
, keep only the preoperatory and the "three months after surgery" time points, enough for the tutorial
If TRUE
, remove samples that do not appear on all timepoints. Useful for the tutorial.
Invisibly, the annotations. See the example for how to download the annotations and create a dataset from the downloaded files.
Besides the destination directory, this function includes three logical parameters to limit the amount of downloaded/saved data. To run the tutorial workflow:
only the "preop" and "three months" timepoints are used,
only subjects measured in both preop and three months time points are used
only the CPMG samples are used.
If you want to run the tutorial, you can set those filters to TRUE
. Then, roughly
800MB will be downloaded, and 77MB of disk space will be used, since for each
downloaded sample we remove all the data but the CPMG.
If you set those filters to FALSE
, roughly 1.8GB of data will be
downloaded (since we have more timepoints to download) and 1.8GB
of disk space will be used.
Note that we have experienced some sporadic timeouts from Metabolights, when downloading the dataset. If you get those timeouts simply re-run the download function and it will restart from where it stopped.
Note as well, that we observed several files to have incorrect data:
Obs4_0346s.zip is not present in the FTP server
Obs0_0110s.zip and Obs1_0256s.zip incorrectly contain sample Obs1_0010s
This function removes all three samples from the samples annotations and doesn't download their data.
if (FALSE) {
download_MTBLS242("./MTBLS242")
annot <- readr::read_tsv(annotations_destfile)
dataset <- nmr_read_samples(annot$filename)
dataset <- nmr_meta_add(dataset, annot)
dataset
}