Select features based on Coefficient of Variation from MultiDataSet

Computes the Coefficient of Variation (COV) for each feature in an omics dataset from a MultiDataSet object, and select features with the highest COV values. This is a wrapper function around the get_dataset_matrix() and select_features_cov_matrix() functions.

Usage

select_features_cov(
  mo_data,
  dataset_name,
  to_keep_n = NULL,
  to_keep_prop = NULL,
  with_ties = TRUE
)

Arguments

mo_data

A MultiDataSet-class object.

dataset_name

Character, name of the omics dataset on which to apply feature pre-selection.

to_keep_n

Integer, the number of features to retain in the dataset. Should be less than the number of features in the dataset. If NULL or NA, to_keep_prop will be used instead.

to_keep_prop

Numeric, the proportion of features to retain in the dataset. Will be ignored if to_keep_n is supplied. Value should be > 0 and < 1.

with_ties

Should ties be kept together? If TRUE, may return more features than requested. Default value is TRUE.

Value

A tibble with columns feature_id, cov and selected (logical, indicates whether the feature is selected based on its COV value). In addition, the name of the dataset filtered is stored in the return object attribute dataset_name (which can be accessed via attr(res, "dataset_name")).