mv_feature_filter {structToolbox} | R Documentation

## Filter by fraction missing values

### Description

Filters features where the percent number of missing values exceeds a predefined threshold.

### Usage

    mv_feature_filter(
      threshold = 20,
      qc_label = "QC",
      method = "QC",
      factor_name,
      ...
    )

### Arguments

`threshold` | (numeric) The threshold for excluding features. The default is `20`.
`qc_label` | (character) The label used to identify QC samples. The default is `"QC"`.
`method` | (character) Filtering method. Allowed values are limited to the following: `"within_all"`: The filter is applied within classes. `"within_one"`: The filter is applied within any one class. `"QC"`: The filter is applied within QC samples. `"across"`: The filter is applied across all samples. The default is `"QC"`.
`factor_name` | (character) The name of a sample-meta column to use.
`...` | Additional slots and values passed to `struct_class`.

### Details

This object makes use of functionality from the following packages:

- `pmp`

### Value

A `mv_feature_filter` object with the following `output` slots:

`filtered` | (DatasetExperiment) A DatasetExperiment object containing the filtered data.
`flags` | (data.frame)

### References

Jankevics A, Lloyd GR, Weber RJM (2021). pmp: Peak Matrix Processing and signal batch correction for metabolomics datasets. R package version 1.5.0.

### Examples

    D = iris_DatasetExperiment()
    M = mv_feature_filter(factor_name='Species',qc_label='versicolor')
    M = model_apply(M,D)

[Package structToolbox version 1.6.1 Index]