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Performs cross-validation to estimate the optimal number of features to retain from each dataset for a DIABLO run.

Usage

diablo_tune(
  mixomics_data,
  design_matrix,
  keepX_list = NULL,
  cpus = NULL,
  seed = NULL,
  ...
)

Arguments

mixomics_data

A mixOmics input object created with get_input_mixomics_supervised().

design_matrix

Either numeric matrix created through diablo_generate_design_matrix, or character (accepted values are 'null', 'weighted_full', 'full'). See Details.

keepX_list

Named list, gives for each omics dataset in the mixOmics input (i.e. excluding the response Y) a vector of values to test (i.e. number of features to return from this dataset). If NULL (default), a standard grid will be applied for each dataset and latent component, testing values: seq(5, 30, 5).

cpus

Integer, the number of CPUs to use when running the code in parallel. For advanced users, see the BPPARAM argument of mixOmics::tune.block.splsda().

seed

Integer, seed to use. Default is NULL, i.e. no seed is set inside the function.

...

Arguments to be passed to the mixOmics::tune.block.splsda() function.

Value

A list, see mixOmics::tune.block.splsda().

Details

The design_matrix`` argument can either be a custom design matrix (for example as constructed via the diablo_generate_design_matrix` function); or a character indicating the type of design matrix to generate. Possible values include:

  • 'null': Off-diagonal elements of the design matrix are set to 0;

  • 'weighted_full': Off-diagonal elements of the design matrix are set to 0.1;

  • 'full': Off-diagonal elements of the design matrix are set to 1.