..Rcheck/tests/testthat/test-analyze_batch.R

test_that("analize_batch", {

  init_env(tempFolder, parallel_strategy = "sequential")

  nitem <- 1e4
  nsamples <- 21

  probe_features <- PROBES_Gene_Whole[!is.na(PROBES_Gene_Whole$START),c("CHR","START","PROBE")]
  probe_features <- unique(probe_features)
  probe_features$END <- probe_features$START

  nitem <- min(nitem, nrow(probe_features))
  probe_features <- probe_features[probe_features$PROBE %in% sample(x=probe_features[,"PROBE"] , size=nitem),]

  methylation_data <- rnorm(nitem*nsamples,mean = 0.5, sd = 0.7)
  methylation_data <- as.data.frame(matrix(methylation_data,nitem,nsamples))

  row.names(methylation_data) <- probe_features$PROBE

  Sample_ID <- stri_rand_strings(nsamples, 15, pattern = "[A-Za-z]")
  colnames(methylation_data) <- Sample_ID
  Sample_Group <- c(rep("Control",nsamples/3),rep("Case",nsamples/3),rep("Reference",nsamples/3))
  sample_sheet <- data.frame(Sample_Group, Sample_ID)

  sliding_window_size <- 11
  bonferroni_threshold <- 0.01
  batch_id <- 1
  iqrTimes <- 3

  sp <- analyze_batch( methylation_data =  methylation_data,
                        sample_sheet =  sample_sheet,
                        sliding_window_size = sliding_window_size,
                        bonferroni_threshold =  bonferroni_threshold,
                        iqrTimes =  iqrTimes,
                        batch_id = batch_id)


  sp$Sample_Group <- sample_sheet$Sample_Group

  # message(nrow(sp))
  # message(nrow(sample_sheet))
  testthat::expect_true(nrow(sp)==nrow(sample_sheet))
  testthat::expect_true(sum(na.omit(sp[,"MUTATIONS_BOTH"])>0)>0)

  future::plan(future::multisession)
})
drake69/semseeker documentation built on Sept. 17, 2023, 12:22 a.m.