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)
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