Surrogate/Internal Standard Recovery

step_measure_surrogate_recovery() creates a specification of a recipe step that calculates recovery percentages for surrogate or internal standards. This is essential for quality control in analytical workflows where spiked compounds are used to monitor method performance.

Usage

step_measure_surrogate_recovery(
  recipe,
  ...,
  expected_col = NULL,
  expected_value = NULL,
  recovery_suffix = "_recovery",
  action = c("add_column", "flag", "filter"),
  flag_col = ".surrogate_pass",
  min_recovery = 70,
  max_recovery = 130,
  role = "surrogate",
  trained = FALSE,
  skip = FALSE,
  id = recipes::rand_id("measure_surrogate_recovery")
)

Arguments

recipe

A recipe object.

...

One or more selector functions to choose surrogate columns (measured concentrations or responses).

expected_col

Name of a column containing expected concentrations for each sample. Mutually exclusive with expected_value.

expected_value

A fixed numeric value for expected concentration. Used when all surrogates have the same expected value. Mutually exclusive with expected_col.

recovery_suffix

Suffix appended to column names for recovery output. Default is "_recovery".

action

What to do with recovery calculations:

"add_column" (default): Add new columns with recovery percentages
"flag": Add a boolean column indicating if recovery is within limits
"filter": Remove rows where any surrogate is outside limits

flag_col

Name of the flag column when action = "flag". Default is ".surrogate_pass".

min_recovery

Minimum acceptable recovery percentage. Default is 70.

max_recovery

Maximum acceptable recovery percentage. Default is 130.

role

Recipe role for new recovery columns. Default is "surrogate".

trained

Logical indicating if the step has been trained.

skip

Logical. Should the step be skipped when baking?

id

Unique step identifier.

Value

An updated recipe with the new step added.

Details

Recovery Calculation

Recovery is calculated as: recovery_pct = (measured / expected) * 100

Where:

measured is the observed concentration/response of the surrogate
expected is the known spike amount or theoretical value

Acceptance Criteria

Typical acceptance limits vary by application:

ICH M10 (Bioanalytical): 70-130% for surrogates
EPA Methods: Often 50-150% or method-specific
FDA Guidance: Application-specific, often 80-120%

Use Cases

Monitor extraction efficiency in sample preparation
Track instrument performance across runs
Identify samples with matrix effects or procedural errors

Examples

library(recipes)

# Example: QC data with spiked surrogates
qc_data <- data.frame(
  sample_id = paste0("QC", 1:10),
  surrogate_1 = rnorm(10, mean = 100, sd = 10),
  surrogate_2 = rnorm(10, mean = 50, sd = 5),
  analyte = rnorm(10, mean = 75, sd = 8)
)

# Add recovery columns for surrogates with expected value of 100 and 50
rec <- recipe(~ ., data = qc_data) |>
  update_role(sample_id, new_role = "id") |>
  step_measure_surrogate_recovery(
    surrogate_1,
    expected_value = 100,
    min_recovery = 80,
    max_recovery = 120
  ) |>
  prep()

bake(rec, new_data = NULL)
#> # A tibble: 10 × 5
#>    sample_id surrogate_1 surrogate_2 analyte surrogate_1_recovery
#>    <chr>           <dbl>       <dbl>   <dbl>                <dbl>
#>  1 QC1              95.7        51.4    71.3                 95.7
#>  2 QC2             101.         55.1    81.6                101. 
#>  3 QC3              91.1        54.1    79.1                 91.1
#>  4 QC4             103.         49.0    70.3                103. 
#>  5 QC5             104.         51.9    67.0                104. 
#>  6 QC6              99.7        45.3    76.2                 99.7
#>  7 QC7              75.3        54.3    74.9                 75.3
#>  8 QC8             126.         47.7    60.7                126. 
#>  9 QC9              97.9        62.1    75.3                 97.9
#> 10 QC10            107.         41.7    76.5                107.