Apply a S3 filter object to a pmartR S3 object

This function takes a filter object of class 'cvFilt', 'rmdFilt', 'moleculeFilt', 'proteomicsFilt', 'imdanovaFilt', 'RNAFilt', 'totalCountFilt', or 'customFilt' and applies the filter to a dataset of pepData, proData, lipidData, metabData, nmrData or seqData.

applyFilt(filter_object, omicsData, ...)

# S3 method for moleculeFilt
applyFilt(filter_object, omicsData, min_num = 2, ...)

# S3 method for totalCountFilt
applyFilt(filter_object, omicsData, min_count, ...)

# S3 method for RNAFilt
applyFilt(
  filter_object,
  omicsData,
  min_nonzero = NULL,
  size_library = NULL,
  ...
)

# S3 method for cvFilt
applyFilt(filter_object, omicsData, cv_threshold = 150, ...)

# S3 method for rmdFilt
applyFilt(
  filter_object,
  omicsData,
  pvalue_threshold = 1e-04,
  min_num_biomolecules = 50,
  ...
)

# S3 method for proteomicsFilt
applyFilt(
  filter_object,
  omicsData,
  min_num_peps = NULL,
  redundancy = FALSE,
  ...
)

# S3 method for imdanovaFilt
applyFilt(
  filter_object,
  omicsData,
  comparisons = NULL,
  min_nonmiss_anova = NULL,
  min_nonmiss_gtest = NULL,
  remove_singleton_groups = TRUE,
  ...
)

# S3 method for customFilt
applyFilt(filter_object, omicsData, ...)

Arguments

filter_object: an object of the class 'cvFilt', 'proteomicsFilt', 'rmdFilt', 'moleculeFilt', 'imdanovaFilt', 'customFilt', 'RNAFilt', or 'totalCountFilt' created by cv_filter, proteomics_filter, rmd_filter, molecule_filter, imdanova_filter, custom_filter, RNA_filter, or total_count_filter, respectively.
omicsData: an object of the class pepData, proData, lipidData, metabData, nmrData, or seqData usually created by as.pepData, as.proData, as.lipidData, as.metabData, as.nmrData, or as.seqData, respectively.
...: further arguments
min_num, min_count, min_nonzero, size_library, cv_threshold, pvalue_threshold, min_num_biomolecules, min_num_peps, redundancy, comparisons, min_nonmiss_anova, min_nonmiss_gtest, remove_singleton_groups: Arguments that depend on the class of filter_object, see details.

Value

An object of the class pepData, proData,

lipidData, metabData, nmrData, or seqData with specified cname_ids, edata_cnames, and emeta_cnames filtered out of the appropriate datasets.

Details

Further arguments can be specified depending on the class of the filter_object being applied.

For a filter_object of type 'moleculeFilt':

min_num an integer value specifying the minimum number of times each biomolecule must be observed across all samples in order to retain the biomolecule. Default value is 2.

For a filter_object of type 'cvFilt':

cv_threshold an integer value specifying the maximum coefficient of variation (CV) threshold for the biomolecules. Biomolecules with CV greater than this threshold will be filtered. Default threshold is 150.

For a filter_object of type 'rmdFilt':

`pvalue_threshold`	numeric value between 0 and 1, specifying the p-value below which samples will be removed from the dataset. Default is 0.001.
`min_num_biomolecules`	numeric value greater than 10 (preferably greater than 50) that specifies the minimum number of biomolecules that must be present in order to create an rmdFilt object. Using values less than 50 is not advised.

For a filter_object of type 'proteomicsFilt' either or both of the following can be applied:

`min_num_peps`	an optional integer value between 1 and the maximum number of peptides that map to a protein in omicsData. The value specifies the minimum number of peptides that must map to a protein. Any protein with less than `min_num_peps` mapping to it will be removed from the dataset. Default value is NULL, meaning that this filter is not applied.
`redundancy`	logical indicator of whether to filter out degenerate/redundant peptides (peptides that map to more than one protein). Default value is FALSE.

For a filter_object of type 'imdanovaFilt':

`min_nonmiss_anova`	integer value specifying the minimum number of non-missing feature values allowed per group for `anova_filter`. Default value is 2.
`min_nonmiss_gtest`	integer value specifying the minimum number of non-missing feature values allowed per group for `gtest_filter`. Default value is 3.

For a filter_object of type 'totalCountFilt':

min_count integer value specifying the minimum number of biomolecule counts observed across all samples in order for the biomolecule to be retained in the dataset. This filter is only applicable for seqData objects.

For a filter_object of type 'RNAFilt' either or both of the following can be applied:

`min_nonzero`	integer value specifying the minimum number of non-zero feature values per sample.
`size_library`	integer value or fraction between 0 and 1 specifying the minimum number of total reads per sample. This filter is only applicable for `seqData` objects.

There are no further arguments for a filter_object of type ' customFilt'.

Author

Lisa Bramer, Kelly Stratton

Examples

library(pmartRdata)
to_filter <- molecule_filter(omicsData = pep_object)
summary(to_filter, min_num = 2)
pep_object2 <- applyFilt(
  filter_object = to_filter,
  omicsData = pep_object, min_num = 2
)
summary(pep_object2) # number of Peptides is as expected based on summary of 
                     # the filter object that was applied
pep_object2 <- group_designation(omicsData = pep_object2,
                                 main_effects = "Phenotype")
to_filter2 <- imdanova_filter(omicsData = pep_object2)
pep_object3 <- applyFilt(
  filter_object = to_filter2,
  omicsData = pep_object2,
  min_nonmiss_anova = 3
)