tests/testthat/test_plotting_fun.R

In MahShaaban/pcr: Analyzing Real-Time Quantitative PCR Data

context("testing plotting functions")

test_that(".pcr_plot_analyze returns a ggplot", {
  ## add grouping variable
  group_var <- rep(c('brain', 'kidney'), each = 6)

  # calculate all values and errors in one step
  res <- pcr_ddct(ct1,
                  group_var = group_var,
                  reference_gene = 'GAPDH',
                  reference_group = 'brain')
  gg <- .pcr_plot_analyze(res, method = 'delta_delta_ct')

  expect_identical(class(gg), c("gg", "ggplot"))

  ct1$c_myc2 <- ct1$c_myc
  res2 <- pcr_ddct(ct1,
                  group_var = group_var,
                  reference_gene = 'GAPDH',
                  reference_group = 'brain')
  gg <- .pcr_plot_analyze(res2, method = 'delta_delta_ct')

  expect_identical(class(gg), c("gg", "ggplot"))

  gg <- .pcr_plot_analyze(res2, method = 'delta_delta_ct', facets = TRUE)

  expect_identical(class(gg), c("gg", "ggplot"))
})

test_that(".pcr_plot_analyze returns a dodge columns plot", {
  ## add grouping variable
  group_var <- rep(c('brain', 'kidney'), each = 6)

  # calculate all values and errors in one step
  res <- pcr_ddct(ct1,
                  group_var = group_var,
                  reference_gene = 'GAPDH',
                  reference_group = 'brain')

  gg <- .pcr_plot_analyze(res, method = 'delta_delta_ct')

  expect_identical(class(gg), c("gg", "ggplot"))
})

test_that(".pcr_plot_analyze returns a faceted plot", {
  ## add grouping variable
  group_var <- rep(c('brain', 'kidney'), each = 6)

  # calculate all values and errors in one step
  res <- pcr_ddct(ct1,
                  group_var = group_var,
                  reference_gene = 'GAPDH',
                  reference_group = 'brain')

  gg <- .pcr_plot_analyze(res, method = 'delta_delta_ct', facets = TRUE)

  expect_identical(class(gg), c("gg", "ggplot"))
})

test_that('.pcr_plot_assess returns an efficiency plot', {
  # make amount/dilution variable
  amount <- rep(c(1, .5, .2, .1, .05, .02, .01), each = 3)

  gg <- .pcr_plot_assess(ct3,
                        amount,
                        reference_gene = 'GAPDH',
                        method = 'efficiency')
  expect_identical(class(gg), c("gg", "ggplot"))
})

test_that('.pcr_plot_assess returns standard_curve plots', {
  # make amount/dilution variable
  amount <- rep(c(1, .5, .2, .1, .05, .02, .01), each = 3)

  gg <- .pcr_plot_assess(ct3,
                        amount,
                        reference_gene = 'GAPDH',
                        method = 'standard_curve')
  expect_identical(class(gg), c("gg", "ggplot"))
})