compute_targetVal — compute_targetVal • malbacR

This function computes the target values for ensemble learning architecture

Usage

compute_targetVal(
  QC_num,
  sampleType,
  batchID = NULL,
  targetVal_method = c("mean", "median"),
  targetVal_batchWise = FALSE,
  targetVal_removeOutlier = !targetVal_batchWise,
  coerce_numeric = FALSE
)

Arguments

QC_num: a numeric data.frame including the metabolite values of quality control (QC) samples. Missing values and infinite values will not be taken into account. Row: sample. Column: metabolite variable. See Examples.
sampleType: a vector corresponding to QC_num to specify the type of each QC sample. QC samples of the same type should have the same type name. See Examples.
batchID: a vector corresponding to QC_num to specify the batch of each sample. Ignored if targetVal_batchWise = FALSE. See Examples.
targetVal_method: a character string specifying how the target values are computed. Can be "mean" (default) or "median". See Details.
targetVal_batchWise: logical. If TRUE, the target values will be computed based on each batch, otherwise, based on the whole dataset. Setting TRUE might be useful if your dataset has very obvious batch effects, but this may also make the algorithm less robust. See Details. Default: FALSE.
targetVal_removeOutlier: logical. If TRUE, outliers will be removed before the computation. Outliers are determined with 1.5 * IQR (interquartile range) rule. We recommend turning this off when the target values are computed based on batches. See Details. Default: !targetVal_batchWise.
coerce_numeric: logical. If TRUE, values in QC_num will be coerced to numeric before the computation. The columns cannot be coerced will be removed (with warnings). See Examples. Default: FALSE.

Value

the function returns a list of length one containing the target values computed on the whole dataset.