Compare Multiple SEC Samples

Compares SEC analysis results across multiple samples, providing a summary table of key metrics and optional overlay plots.

Usage

measure_sec_compare(
  ...,
  samples = NULL,
  metrics = c("mw_averages", "mwd", "branching"),
  plot = TRUE,
  reference = 1,
  digits = 2
)

Arguments

...

Data frames containing SEC results. Each should be a baked recipe output with measure columns (MW, concentration, etc.).

samples

Character vector of sample names. If NULL, uses names from ... or generates sequential names ("Sample 1", "Sample 2", etc.).

metrics

Character vector specifying which metrics to compare. Options:

• "mw_averages": Mn, Mw, Mz, dispersity

• "mwd": Molecular weight distribution overlap

• "branching": Branching metrics (if available)

Default includes all available metrics.

plot

Logical. Generate MWD comparison plot? Default is TRUE. Note: Plot is only generated when "mwd" is included in metrics.

reference

Integer or character. Which sample to use as reference for percent differences. Default is 1 (first sample).

digits

Integer. Number of decimal places for numeric values. Default is 2. Must be non-negative.

Value

A list of class sec_comparison containing:

summary

Tibble with comparison metrics for all samples

differences

Tibble with absolute and percent differences vs reference

plot

ggplot2 object (if plot = TRUE and "mwd" in metrics), otherwise NULL

samples

Character vector of sample names

reference

Name of reference sample

Details

This function is useful for:

• Batch-to-batch comparison

• Stability studies

• Process optimization

• Quality control

Input Data Handling:

When input data frames contain multiple rows (e.g., multiple injections), numeric metrics are averaged across rows. For single-row data frames (typical for processed SEC results), values are used directly.

The function recognizes molecular weight columns with either naming convention: prefixed (mw_mn, mw_mw, mw_mz, mw_dispersity) or standard (Mn, Mw, Mz, dispersity).

Comparison Metrics:

MW Averages: Compares Mn, Mw, Mz, and dispersity with absolute and percent differences from the reference sample.

MWD Overlay: Creates overlaid MWD plots showing distribution differences. Useful for detecting bimodality, tailing, or distribution shifts.

Branching: Compares branching index and frequency if available from triple-detection data.

See also

Other sec-export: measure_sec_report(), measure_sec_slice_table(), measure_sec_summary_table()

Examples

if (FALSE) { # \dontrun{
# Compare three batches
comparison <- measure_sec_compare(
  batch1_data,
  batch2_data,
  batch3_data,
  samples = c("Batch 1", "Batch 2", "Batch 3")
)

# View summary table
comparison$summary

# View differences from reference
comparison$differences

# Display overlay plot
comparison$plot

# Compare only MW averages without plot
comparison <- measure_sec_compare(
  sample_a, sample_b,
  metrics = "mw_averages",
  plot = FALSE
)
} # }