blank_filter {structToolbox} | R Documentation

## Blank filter

### Description

Filters features based on the features present in blank samples. The median intensity of the samples is compared to the median intensity of the blank samples. Any sample not sufficiently more intense than the blank is removed. This is a wrapper for the blank filter in the PMP package.

### Usage

    blank_filter(
      fold_change = 20,
      blank_label = "blank",
      qc_label = "QC",
      factor_name,
      fraction_in_blank = 0,
      ...
    )

### Arguments

`fold_change` | `numeric(1)`, fold_change minimum fold change between analytical and blank samples.
`blank_label` | `character(1)`, class label used to identify blank samples.
`qc_label` | `character(1)` or `NULL`, class label used to identify QC samples.
`factor_name` | the column name of sample_meta to use
`fraction_in_blank` | `numeric(1)`, value between 0 to 1 to specify fraction in how many blanks peaks should be present.
`...` | additional slots and values passed to struct_class

### Value

A struct model object for applying a blank filter

### Examples

    D = iris_DatasetExperiment()
    M = blank_filter(fold_change=2,
                     factor_name='Species',
                     blank_label='setosa',
                     qc_label='versicolor')
    M = model_apply(M,D)

[Package structToolbox version 1.0.1 Index]