tests/testthat/test-normalize.R

In proBatch: Tools for Diagnostics and Corrections of Batch Effects in Proteomics

context("normalize")

test_that("quantile_normalize", {
  data(example_proteome_matrix, package="proBatch")
  
  matrix_test <- example_proteome_matrix[1:10, ]
  quant_normalized_matrix <- quantile_normalize_dm(matrix_test)

  quant_matrix <- preprocessCore::normalize.quantiles(matrix_test)
  
  expect_equivalent(quant_matrix[1:10], quant_normalized_matrix[1:10])
})



test_that("normalize_sample_medians", {
  data(example_proteome, package="proBatch")
  
  samples <- c("I170925_BXD66_HF_ET1560_SW_Run001", 
               "I170925_BXD101_CD_ET1424_SW_Run002", 
               "I170925_BXD63_HF_ET1715_SW_Run003", 
               "I170925_BXD61_HF_ET1721_SW_Run004")
  sampled_rows = example_proteome$FullRunName %in% samples
  sample_df <- example_proteome[sampled_rows, ]
  median_centered_data <- normalize_sample_medians_df(sample_df, 
                                                      keep_all = 'all')

  expect_equivalent(median_centered_data$median_global[1], 30277.6, tolerance = 1e-2)
  expect_equivalent(median_centered_data$median_run[2], 29252.14, tolerance = 1e-2)
  
  expect_equivalent(median_centered_data$Intensity[1], 2728887.42, tolerance = 1e-2)
  expect_equivalent(median_centered_data$Intensity[549], 35191.95, tolerance = 1e-2)
  expect_equivalent(median_centered_data$preNorm_Intensity[549], 25479.8)
  
})