View source: R/mv_feature_filter_class.R
| mv_feature_filter | R Documentation | 
Removes features where the percentage of non-missing values falls below a threshold.
mv_feature_filter(
  threshold = 20,
  qc_label = "QC",
  method = "QC",
  factor_name,
  ...
)
| threshold | (numeric) The minimum percentage of non-missing values. The default is  | 
| qc_label | (character) The label used to identify QC/group samples when using the "QC" (within a named group) filtering method. The default is  | 
| method | (character) Filtering method. Allowed values are limited to the following: 
  The default is  | 
| factor_name | (character) The name of a sample-meta column to use. | 
| ... | Additional slots and values passed to  | 
This object makes use of functionality from the following packages:
pmp
A  mv_feature_filter object with the following output slots:
| filtered | (DatasetExperiment) A DatasetExperiment object containing the filtered data. | 
| flags | (data.frame) % missing values and a flag indicating whether the sample was rejected. 0 = rejected. | 
A mv_feature_filter object inherits the following struct classes: 
[mv_feature_filter] >> [model] >> [struct_class]
Jankevics A, Lloyd GR, Weber RJM (????). pmp: Peak Matrix Processing and signal batch correction for metabolomics datasets. R package version 1.15.1.
M = mv_feature_filter(
      threshold = 20,
      qc_label = "QC",
      method = "QC",
      factor_name = "V1")
D = iris_DatasetExperiment()
M = mv_feature_filter(factor_name='Species',qc_label='versicolor')
M = model_apply(M,D)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.