Skip to contents

Automatic Removing Variables

auto_remove.Rd

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.

Usage

auto_remove(exp, preset = "discovery", group_col = "group")

Arguments

exp

A glyexp::GlycomicSE(), glyexp::GlycoproteomicSE(), or SummarizedExperiment::SummarizedExperiment() 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.

Value

The filtered input container, with its class preserved.

Examples

library(glyexp)
exp <- real_experiment
auto_remove(exp)
#> ℹ Applying preset "discovery"...
#> ℹ Total removed: 24 (0.56%) variables.
#> 
#> ── GlycoproteomicSE ────────────────────────────────────────────────────────────
#> ℹ Abundance assay: 12 samples, 4238 variables
#> ℹ Glycan type: N
#> ℹ Row data fields: peptide <chr>, peptide_site <int>, protein <chr>, protein_site <int>, gene <chr>, glycan_composition <comp>, glycan_structure <struct>
#> ℹ Column data fields: group <fct>
#> ℹ Metadata fields: exp_type <chr>, glycan_type <chr>, quant_method <chr>