applyFilt: Apply a S3 filter object to a pmartR S3 object

In pmartR/pmartR: Panomics Marketplace - Quality Control and Statistical Analysis for Panomics Data

Apply a S3 filter object to a pmartR S3 object

Description

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.

Usage

applyFilt(filter_object, omicsData, ...)

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

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

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

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

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

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

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

## S3 method for class '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.

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'.

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.

Author(s)

Lisa Bramer, Kelly Stratton

See Also

molecule_filter

imdanova_filter

rmd_filter

cv_filter

proteomics_filter

custom_filter

RNA_filter

total_count_filter

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
)

pmartR/pmartR documentation built on April 24, 2024, 10:22 p.m.