retrieveMetadata: Download data from magma of one model, but transformed into...
In magmaR: R-Client for 'Magma' of the 'UCSF Mount Etna Data Library'

Description Usage Arguments Details Value See Also Examples

Retrieve data from one model ("meta") transformed into the shape of linked records of a different model ("target"). For example, one could get subject-level information for an RNAseq counts matrix with this function. The output would contain columns of subject-level attributes, and rows that are the RNAseq-model records.

retrieveMetadata(
  target,
  projectName,
  meta_modelName,
  meta_attributeNames = "all",
  target_modelName,
  target_recordNames = "all",
  ...
)

`target`	A list, which can be created using `magmaRset`, containing your authorization 'token' (a string), a 'url' of magma to target (a string), and optional 'opts' for specifying additions parameters for curl requests (a named list).
`projectName`	Single string. The name of the project you would like to interact with. For options, see `retrieveProjects`.
`meta_modelName, meta_attributeNames`	Strings which indicate the "meta"data to retrieve. They work the same as inputs of other functions without the `meta_` portion.
`target_modelName, target_recordNames`	Strings which indicate the "target" data that meta-data is desired to be reshaped into. They work the same as inputs of other functions without the `target_` portion, and these inputs ultimately set which records of "meta" model data to actually obtain.
`...`	Additional parameters passed along to the internal '.retrieve()', '.query()', or '.update()' functions, for troubleshooting or advanced-user purposes only: `request.only` (Logical) & `json.params.only` (Logical) which 1) stop the function before its main curl request to magma and 2) returns the values that would have been sent to magma in either of two formats. `verbose` (Logical) sets whether to report the status of the curl request after it is performed.

This function retrieves data from one model (the "meta" model) transformed so that rows of the returned dataframe correspond to records of a different model (the "target" model).

Internally, it first determines the path, through child-parent model linkages, to navigate from the meta_model to the target_model.

Then, it performs calls to query in order to retrieve identifier linkage along that path. The identifier linkage is turned into a dataframe of identifier traces.

Next, it performs a call to retrieve to obtain the wanted metadata as a dataframe.

(If linkage paths would create any 1:many mappings of target data records to metadata records, data of extra records are shifted "rightwards" into columns appended with "_#" in their names. This is a reliable, though imperfect, method so we hope to implement alternatives in the future.)

Finally, the dataframe of linkage path identifiers is merged with the metadata dataframe, reshaping the metadata to properly have one row per requested target_recordName.

A dataframe with rows = target_recordNames and columns = model identifiers and either meta_attributeNames or repeats of meta_attributeNames_# when there are 1:many mappings of target data records to metadata records.

retrieve and retrieveMatrix which will likely be useful for retrieving associated "target" data.

if (interactive()) {
    # First, we use magmaRset to create an object which will tell other magmaR
    #  functions our authentication token (as well as some other optional bits).
    # When run in this way, it will ask you to give your token.
    magma <- magmaRset()
    
    # Running like this will ask for input of your janus token one time.
    retrieveMetadata(
        target = magma,
        projectName = "example",
        meta_modelName = "subject",
        meta_attributeNames = "group",
        target_modelName = "rna_seq",
        target_recordNames = "all")
}