Extract Slice-by-Slice SEC Data

Extracts point-by-point (slice) data from SEC analysis results, creating a long-format table suitable for export or further analysis.

Usage

measure_sec_slice_table(
  data,
  measures = NULL,
  sample_id = NULL,
  include_location = TRUE,
  pivot = FALSE
)

Arguments

data

A data frame containing SEC results with measure columns.

measures

Character vector of measure column names to include. If NULL, includes all measure columns found.

sample_id

Column name containing sample identifiers. If NULL, uses row numbers.

include_location

Logical. Include the location (time/volume) column? Default is TRUE.

pivot

Logical. Pivot measures to wide format (one column per measure)? Default is FALSE (long format).

Value

A tibble with slice-by-slice data:

sample_id

Sample identifier

slice

Slice index (1, 2, 3, ...)

location

Elution time or volume

measure

Measure column name (if pivot = FALSE)

value

Signal value (if pivot = FALSE)

<measure_names>

Individual measure columns (if pivot = TRUE)

Details

This function extracts the raw slice data from processed SEC chromatograms, making it easy to:

• Export to CSV/Excel for external analysis

• Create custom plots

• Perform slice-level calculations

• Compare samples point-by-point

Typical Slice Data Columns:

• Retention time/volume (location)

• Concentration (from RI or UV)

• Molecular weight (from calibration or MALS)

• Intrinsic viscosity (from viscometer)

• Radius of gyration (from MALS angles)

• Composition (from UV/RI ratio)

See also

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

Examples

if (FALSE) { # \dontrun{
library(recipes)
library(measure)

# Process SEC data
prepped <- recipe(~., data = sec_triple_detect) |>
  step_measure_input_long(ri, location = vars(time), col_name = "ri") |>
  step_sec_baseline() |>
  prep() |>
  bake(new_data = NULL)

# Extract slice table (long format)
slices <- measure_sec_slice_table(prepped, measures = "ri")

# Extract slice table (wide format)
slices_wide <- measure_sec_slice_table(
  prepped,
  measures = c("ri", "mw"),
  pivot = TRUE
)

# Export to CSV
write.csv(slices, "sec_slices.csv", row.names = FALSE)
} # }