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Standardize Sample Type Values

Source: R/metadata-validation.R
measure_standardize_sample_type.Rd

Converts non-standard sample type values to canonical form using a user-specified mapping. This is useful when data uses different naming conventions (e.g., "QC", "quality_control", "pooled_qc").

Usage

measure_standardize_sample_type(
  data,
  col = "sample_type",
  mapping = NULL,
  unknown_action = c("error", "warn", "keep", "unknown")
)

Arguments

data

A data frame containing a sample type column.

col

Name of the sample type column. Default is "sample_type".

mapping

A named list mapping canonical types to vectors of aliases. For example: list(qc = c("QC", "quality_control", "pooled_qc")). If NULL, uses default case-insensitive matching.

unknown_action

What to do with values that don't match any mapping:

  • "error" (default): Stop with error

  • "warn": Warn and keep original value

  • "keep": Silently keep original value

  • "unknown": Convert to "unknown"

Value

The data frame with standardized sample_type values.

Examples

# Data with non-standard sample types
data <- data.frame(
  sample_id = 1:5,
  sample_type = c("QC", "STD", "BLK", "UNK", "REF")
)

# Standardize with custom mapping
measure_standardize_sample_type(
  data,
  mapping = list(
    qc = c("QC", "qc", "quality_control"),
    standard = c("STD", "std", "cal"),
    blank = c("BLK", "blk", "blank"),
    unknown = c("UNK", "unk", "sample"),
    reference = c("REF", "ref")
  )
)
#>   sample_id sample_type
#> 1         1          qc
#> 2         2    standard
#> 3         3       blank
#> 4         4     unknown
#> 5         5   reference