Fun_MAE_to_taskFunc: Convert MAE to mlr task

In drorberel/Bioc2mlr:

Description

Convert MAE to mlr task

Usage

Fun_MAE_to_taskFunc(MAE_obj, param.Y.name, param.covariates,
  param_positive_y_level, task_type)

Arguments

MAE_obj	MAE class
param.Y.name	Vector of dependent variable name
param.covariates	Vector of coaraiate variable(s) name
param_positive_y_level	if ClassifTask, value (character or numeric) to be considered as the positive factor outcome

Details

In case of individual MAE assay (omic) with multiple sub-assays, only first sub-assay will be used. MAE's helpers functions longFormat and wideFormat may not be best candidates, since mlr's functional data require complete subject structure for all 'assays' ('functionals'). this can be achieved by either removing non-complete subjects, or by creating dummy entities with NA. (which can later be imputed if required).

Either ClassifTask or RegrTask will be returned, based on the type of the param.Y.name variable

Value

mlr's ClassifTask or RegrTask

Examples

data(miniACC, package = 'MultiAssayExperiment') # ExpressionSet
miniACC
Fun_MAE_to_taskFunc(miniACC, param.Y.name = 'vital_status', param.covariates = c('gender','days_to_death'), param_positive_y_level = '1')

drorberel/Bioc2mlr documentation built on May 16, 2019, 5 a.m.