Automatic Removing Variables — auto

This function uses preset rules to remove variables with low quality. Available presets:

"simple": remove variables with more than 50% missing values.
"discovery": more lenient, remove variables with more than 80% missing values, but ensure less than 50% of missing values in at least one group.
"biomarker": more strict, remove variables with more than 40% missing values, and ensure less than 60% of missing values in all groups.

QC samples will not be considered in the removal process.

Usage

auto_remove(
  exp,
  preset = "discovery",
  group_col = "group",
  qc_name = "QC",
  info = NULL
)

Arguments

exp: A glyexp_experiment object.
preset: One of "simple", "discovery", or "biomarker". Default "discovery" if group information is available, otherwise "simple".
group_col: The column name in sample_info for groups. Default is "group". Can be NULL when no group information is available.
qc_name: The name of QC samples in the group_col column. Default is "QC". Only used when group_col is not NULL.
info: Internal parameter used by auto_clean().

Value

A modified glyexp::experiment() object.

Examples

library(glyexp)
exp <- real_experiment
auto_remove(exp)
#> No QC samples found. Using all samples.
#> Applying preset "discovery"...
#> Total removed: 24 (0.56%) variables.
#> 
#> ── Glycoproteomics Experiment ──────────────────────────────────────────────────
#> ℹ Expression matrix: 12 samples, 4238 variables
#> ℹ Sample information fields: group <fct>
#> ℹ Variable information fields: peptide <chr>, peptide_site <int>, protein <chr>, protein_site <int>, gene <chr>, glycan_composition <glyrpr_c>, glycan_structure <glyrpr_s>