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measure.sec

Overview

measure.sec is an R package that extends the measure package with preprocessing and analysis steps for Size Exclusion Chromatography (SEC) and Gel Permeation Chromatography (GPC) data.

Features

  • Multi-detector support: RI, UV/DAD, MALS, LALS, RALS, DLS, and viscometer processing
  • Inter-detector delay correction: Align signals from detectors in series
  • Molecular weight calculations: Mn, Mw, Mz, dispersity (PDI)
  • Copolymer composition: UV/RI ratio and composition analysis
  • Protein SEC: Aggregate and fragment quantitation (HMWS/LMWS)
  • Universal calibration: Mark-Houwink parameter-based MW conversion
  • Quality control: System suitability testing (resolution, plate count, asymmetry)
  • Polymer analysis: Branching indices and Mark-Houwink parameter estimation

Package Workflow

SEC Data Analysis Workflow

The typical SEC analysis workflow processes raw chromatogram data through preprocessing, detector-specific signal processing, calibration, and molecular weight calculations. Concentration detectors (RI, UV) require calibration curves from standards, while light scattering detectors (MALS) provide absolute molecular weight directly.

Installation

You can install the development version of measure.sec from GitHub with:

# install.packages("pak")
pak::pak("JamesHWade/measure-sec")

Note: measure.sec requires the measure package:

pak::pak("JamesHWade/measure")

Quick Start 

library(measure)
library(measure.sec)
library(recipes)

# Load example triple-detection SEC data
data(sec_triple_detect, package = "measure.sec")

# Create a processing recipe
rec <- recipe(~ ., data = sec_triple_detect) |>
  # Convert to measure format
  step_measure_input_long(ri_signal, location = vars(elution_time), col_name = "ri") |>
  step_measure_input_long(uv_signal, location = vars(elution_time), col_name = "uv") |>

  # Correct inter-detector delays
  step_sec_detector_delay(
    reference = "ri",
    delay_volumes = c(uv = -0.05)
  ) |>

  # Apply baseline correction
  step_sec_baseline() |>

  # Process RI detector with dn/dc
  step_sec_ri(dn_dc_column = "dn_dc")

# Prep and bake
prepped <- prep(rec)
result <- bake(prepped, new_data = NULL)

Available Steps

Detector Processing

Step Description
step_sec_ri() RI detector with dn/dc normalization
step_sec_uv() UV detector with extinction coefficient
step_sec_dad() Diode array detector processing (multi-wavelength UV)
step_sec_mals() Multi-angle light scattering for absolute MW
step_sec_lals() Low-angle light scattering for absolute MW
step_sec_rals() Right-angle light scattering for absolute MW
step_sec_dls() Dynamic light scattering for Rh and diffusion
step_sec_viscometer() Differential viscometer processing
step_sec_concentration() Convert signal to concentration
step_sec_intrinsic_visc() Intrinsic viscosity calculation

Preprocessing

Step Description
step_sec_detector_delay() Correct inter-detector volume delays
step_sec_baseline() SEC-optimized baseline correction

Molecular Weight

Step Description
step_sec_mw_averages() Calculate Mn, Mw, Mz, dispersity
step_sec_mw_fractions() Calculate MW fractions above/below cutoffs
step_sec_mw_distribution() Generate differential/cumulative MWD
step_sec_conventional_cal() Narrow standard calibration (polynomial fits)
step_sec_universal_cal() Universal calibration with Mark-Houwink

Composition Analysis

Step Description
step_sec_uv_ri_ratio() UV/RI ratio for heterogeneity detection
step_sec_composition() Copolymer composition from UV/RI

Protein SEC

Step Description
step_sec_protein() Complete protein SEC workflow (baseline + aggregates + oligomers)
step_sec_aggregates() HMWS/monomer/LMWS quantitation
step_sec_oligomer() Detailed oligomer species analysis

Quality Control Functions 

# Peak resolution
Rs <- measure_sec_resolution(
  retention_1 = 8.5,
  retention_2 = 10.0,
  width_1 = 0.3,
  width_2 = 0.35
)

# Plate count
N <- measure_sec_plate_count(retention = 10.0, width = 0.25)

# System suitability testing
peaks <- data.frame(
  name = c("dimer", "monomer"),
  retention = c(8.5, 10.0),
  width = c(0.3, 0.35),
  area = c(5, 95)
)

sst <- measure_sec_suitability(
  peaks = peaks,
  reference_peaks = c("dimer", "monomer")
)
print(sst)

Polymer Analysis Functions 

# Estimate Mark-Houwink parameters
mw <- c(10000, 25000, 50000, 100000, 250000)
iv <- c(0.15, 0.28, 0.45, 0.72, 1.2)

mh <- measure_mh_parameters(mw, iv)
print(mh)
# K = 1.14e-04, a = 0.716

# Calculate branching index
g <- measure_branching_index(
  mw = mw,
  rg = c(8, 12, 18, 28, 45),
  reference = data.frame(mw = mw, rg = c(10, 15, 22, 35, 55)),
  method = "g"
)

Data Export 

# Extract slice-by-slice data
slices <- measure_sec_slice_table(result, measures = c("ri", "mw"))

# Generate summary table
summary <- measure_sec_summary_table(result, sample_id = "sample_id")

Example Dataset

The package includes sec_triple_detect, a synthetic multi-detector SEC dataset with:

  • 12 polymer samples (PS standards, PMMA, PEG, copolymers)
  • RI, UV, and MALS detector signals
  • Known molecular weights and dispersities
  • Sample-specific dn/dc and extinction coefficients
data(sec_triple_detect)
head(sec_triple_detect)

Integration with measure

measure.sec automatically registers with the measure package on load:

library(measure)
library(measure.sec)

# View registered SEC steps
measure_steps(techniques = "SEC/GPC")

Learn More

For detailed workflows and examples, see the package vignettes:

Getting Help

Code of Conduct

Please note that the measure.sec project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.