Minimum number of measured values filter — filter_na

The number of measured values is counted for each feature, and any feature with less than a predefined minimum number of values in each group is removed. If there are several factors, then the threshold is applied so that the minimum number of samples is present for all combinations (interactions) of groups.

Usage

filter_na_count(threshold, factor_name, ...)

Arguments

threshold: (numeric) The minimum number of samples in each group/interaction.
factor_name: (character) The name of a sample-meta column to use.
...: Additional slots and values passed to struct_class.

Value

A filter_na_count object with the following output slots:

`filtered`	(DatasetExperiment) A DatasetExperiment object containing the filtered data.
`count`	(data.frame) The number of measured values in each group/interaction.
`na_count`	(data.frame) The number of missing values in each group/interaction.
`flags`	(data.frame) Flags to indicate which features were removed.

Inheritance

A filter_na_count object inherits the following struct classes:

[filter_na_count] >> [model] >> [struct_class]

Examples

M = filter_na_count(
      threshold = 2,
      factor_name = "V1")

D = MTBLS79_DatasetExperiment()
M = filter_na_count(threshold=3,factor_name='Class')
M = model_apply(M,D)