Setup a tidy table compatible with a AnalysisConfiguration

Extracts columns relevant for a configuration from a data frame and create new columns e.g. sampleName column etc.

Usage

setup_analysis(data, configuration, debug = FALSE)

Arguments

data

data.frame

configuration

AnalysisConfiguration

debug

if FALSE (default) and any hierarchy-key/sample combination has more than one observation, stop with an informative error. If TRUE, warn and return the diagnostic count table (inspect rows where n > 1) instead.

Value

A tibble with the columns relevant for configuration (sample, hierarchy, factor and response columns). Stops if any hierarchy-key/sample combination is observed more than once (unless debug = TRUE).

See also

Other configuration: AnalysisConfiguration, ContrastConfiguration, INTERNAL_FUNCTIONS_BY_FAMILY, R6_extract_values(), complete_cases(), list_to_ContrastConfiguration(), make_interaction_column(), make_reduced_hierarchy_config(), sample_subset(), separate_hierarchy(), table_factors(), table_factors_size()

Examples

# Example with a normValue column (e.g., creatinine)
set.seed(1234)
data <- sim_lfq_data(Nprot = 10, PEPTIDE = TRUE, N = 4)
data$nr_children <- 1
data$isotopeLabel <- "light"
data$qValue <- 0

# Add creatinine values per sample (not per protein/peptide)
sample_creatinine <- data |> dplyr::select(sample) |> dplyr::distinct() |>
  dplyr::mutate(creatinine = rnorm(dplyr::n(), mean = 100, sd = 10))
data <- dplyr::inner_join(data, sample_creatinine, by = "sample")

config <- AnalysisConfiguration$new()
config$file_name = "sample"
config$factors["group_"] = "group"
config$hierarchy[["protein_Id"]] = c("proteinID", "idtype2")
config$hierarchy[["peptide_Id"]] = "peptideID"
config$set_response("abundance")
config$norm_value = "creatinine"

adata <- setup_analysis(data, config)
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done