filterGridSearchResults: Perform complex feature grid search filter

In CCprofiler/CCprofiler: Complex feature detection using SEC protein chromatograms.

Description

Perform quality filtering of the feature finding result with different cutoffs (grid serch). All possible combinations of the specified parameters are tested.

Usage

filterGridSearchResults(grid_search_results, peak_corr_cutoffs = c(0.5,
  0.75, 0.9), feature_completeness_cutoffs = c(0, 0.5, 1),
  hypothesis_completeness_cutoffs = c(0.5, 1),
  n_subunits_cutoffs = c(2, 3, 4), monomer_distance_cutoffs = c(1, 2),
  remove_decoys = FALSE)

Arguments

grid_search_results	List containing result tables from a feature finding grid search.
peak_corr_cutoffs	Numeric, vector of within peak correlation_cutoff values to test. Between -1 and 1. Default is c(0.5,0.75,0.9).
feature_completeness_cutoffs	Numeric, vector of feature completeness cutoffs to test. Between 0 and 1. Default is c(0,0.5,1).
hypothesis_completeness_cutoffs	Numeric, vector of hypothesis completeness cutoffs to test. Between 0 and 1. Default is c(0.5,1).
n_subunits_cutoffs	Positive integer vector of minimum number of subunits per hypothesis cutoffs to test. Default is c(2,3,4).
monomer_distance_cutoffs	Positive numeric, factor of allowed distance to monomer weight to test. Default is c(1,2).
remove_decoys	Logical, whether to remove the decoys from the result. Default=FALSE.

Value

List of search result tables for every possible parameter combination. The result tables contain additional columns specifying the parameters.

List with stats

Examples

#------------------------
## Complex level
#------------------------

## Load example data into list to simulate grid search results
complexFeaturesGrid <- list(exampleComplexFeatures)

## Perform the filter grid search
complexFeaturesGridFiltered <- filterGridSearchResults(complexFeaturesGrid,
                                                       peak_corr_cutoffs = c(0.5,0.75,0.9),
                                                       feature_completeness_cutoffs = c(0,0.5,1),
                                                       hypothesis_completeness_cutoffs = c(0.5,1),
                                                       n_subunits_cutoffs = c(2,3,4),
                                                       monomer_distance_cutoffs = c(1,2),
                                                       remove_decoys=FALSE)
#------------------------
## Protein level
#------------------------

## Load example data into list to simulate grid search results
proteinFeaturesGrid <- list(exampleProteinFeatures)

## Perform the filter grid search
 proteinFeaturesGridFiltered <- filterGridSearchResults(proteinFeaturesGrid,
                                                        peak_corr_cutoffs = c(0.5,0.75,0.9),
                                                        feature_completeness_cutoffs = c(0,0.5,1),
                                                        hypothesis_completeness_cutoffs = c(0.5,1),
                                                        n_subunits_cutoffs =c(2,3,4),
                                                        monomer_distance_cutoffs = c(0,1),
                                                        remove_decoys=FALSE)

CCprofiler/CCprofiler documentation built on May 19, 2021, 7:40 p.m.