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The constructor of MAETealDataset

mae_dataset.Rd

[Deprecated]

Usage 

mae_dataset(
  dataname,
  x,
  label = data_label(x),
  code = character(0),
  vars = list()
)

Arguments

dataname

(character) a given name for the dataset, it cannot contain spaces

x

(MultiAssayExperiment)

label

(character) label to describe the dataset

code

(character) a character string defining the code needed to produce the data set in x

vars

(named list) in case when this object code depends on other TealDataset object(s) or other constant value, this/these object(s) should be included as named element(s) of the list. For example if this object code needs ADSL object we should specify vars = list(ADSL = <adsl object>). It's recommended to include TealDataset or TealDatasetConnector objects to the vars list to preserve reproducibility. Please note that vars are included to this object as local vars and they cannot be modified within another dataset.

Examples 

# Simple example
utils::data(miniACC, package = "MultiAssayExperiment")
mae_d <- dataset("MAE", miniACC)
mae_d$get_dataname()
#> [1] "MAE"
mae_d$get_dataset_label()
#> character(0)
mae_d$get_code()
#> [1] ""
mae_d$get_raw_data()
#> A MultiAssayExperiment object of 5 listed
#>  experiments with user-defined names and respective classes.
#>  Containing an ExperimentList class object of length 5:
#>  [1] RNASeq2GeneNorm: SummarizedExperiment with 198 rows and 79 columns
#>  [2] gistict: SummarizedExperiment with 198 rows and 90 columns
#>  [3] RPPAArray: SummarizedExperiment with 33 rows and 46 columns
#>  [4] Mutations: matrix with 97 rows and 90 columns
#>  [5] miRNASeqGene: SummarizedExperiment with 471 rows and 80 columns
#> Functionality:
#>  experiments() - obtain the ExperimentList instance
#>  colData() - the primary/phenotype DataFrame
#>  sampleMap() - the sample coordination DataFrame
#>  `$`, `[`, `[[` - extract colData columns, subset, or experiment
#>  *Format() - convert into a long or wide DataFrame
#>  assays() - convert ExperimentList to a SimpleList of matrices
#>  exportClass() - save data to flat files