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Identification overview

Source: R/summarize.R
summarize_experiment.Rd

This function summarizes the number of glycan compositions, glycan structures, glycopeptides, peptides, glycoforms, glycoproteins, and glycosites in an experiment().

Usage

summarize_experiment(x, count_struct = NULL)

Arguments

x

An experiment() object.

count_struct

For counting glycopeptides and glycoforms. whether to count the number of glycan structures or glycopeptides. If TRUE, glycopeptides or glycoforms bearing different glycan structures with the same glycan composition are counted as different ones. If not provided (NULL), defaults to TRUE if glycan_structure column exists in the variable information tibble, otherwise FALSE.

Value

A tibble with columns item and n summarizing the results. The items include:

  • total_composition: The number of glycan compositions.

  • total_structure: The number of glycan structures.

  • total_peptide: The number of peptides.

  • total_glycopeptide: The number of unique combinations of peptides, sites, and glycans.

  • total_glycoform: The number of unique combinations of proteins, sites, and glycans.

  • total_protein: The number of proteins.

  • total_glycosite: The number of unique combinations of proteins and sites.

In addition, _per_sample items are calculated as the average number of detected items per sample. For example, composition_per_sample is the average number of glycan compositions detected per sample.

Details

The following columns are required in the variable information tibble:

  • composition: glycan_composition

  • structure: glycan_structure

  • peptide: peptide

  • glycopeptide: glycan_composition or glycan_structure, peptide, peptide_site

  • glycoform: glycan_composition or glycan_structure, protein or proteins, protein_site or protein_sites

  • protein: protein or proteins

  • glycosite: protein or proteins, protein_site or protein_sites

You can use count_struct parameter to control how to count glycopeptides and glycoforms, either by glycan structures or by glycan compositions.

Examples

exp <- real_experiment
summarize_experiment(exp)
#> # A tibble: 14 × 2
#>    item                        n
#>    <chr>                   <dbl>
#>  1 total_composition        477 
#>  2 total_structure          968 
#>  3 total_peptide            323 
#>  4 total_glycopeptide      4262 
#>  5 total_glycoform         4001 
#>  6 total_protein            162 
#>  7 total_glycosite          276 
#>  8 composition_per_sample   460.
#>  9 structure_per_sample     924.
#> 10 peptide_per_sample       311 
#> 11 glycopeptide_per_sample 3923.
#> 12 glycoform_per_sample    3705 
#> 13 protein_per_sample       156.
#> 14 glycosite_per_sample     268.