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Run calibration check

Source: R/s4_analysis_functs_2.R
run_calibration_check.Rd

run_calibration_check() runs the calibration check. The calibration check involves applying sceptre to analyze negative control target-response pairs — pairs for which we know there is no association between the target and response — to ensure control of the false discovery rate. The calibration check enables us to verify that the discovery set that sceptre ultimately produces is not contaminated by excess false positives. See Chapter 5 of the manual for more detailed information about this function.

Usage

run_calibration_check(
  sceptre_object,
  n_calibration_pairs = NULL,
  calibration_group_size = NULL,
  print_progress = TRUE,
  parallel = FALSE,
  n_processors = "auto",
  log_dir = tempdir(),
  output_amount = 1
)

Arguments

sceptre_object

a sceptre_object

n_calibration_pairs

(optional) the number of negative control pairs to construct and test for association

calibration_group_size

(optional) the number of negative control gRNAs to randomly assemble to form each negative control target

print_progress

(optional; default TRUE) a logical indicating whether to print progress updates

parallel

(optional; default FALSE) a logical indicating whether to run the function in parallel. parallel = TRUE is recommended only on Mac; it is not supported on Windows and may behave unreliably on Linux clusters.

n_processors

(optional; default "auto") an integer specifying the number of processors to use if parallel is set to TRUE. The default, "auto", uses half the physical cores. The fraction may be tuned via the parallelly.availableCores.fraction R option.

log_dir

(optional; default tempdir()) a string indicating the directory in which to write the log files (ignored if parallel = FALSE)

output_amount

(optional; default 1) an integer taking values 1, 2, or 3 specifying the amount of information to return. 1 returns the least amount of information and 3 the most.

Value

an updated sceptre_object in which the calibration check has been carried out

Examples

data(highmoi_example_data)
data(grna_target_data_frame_highmoi)
# import data
sceptre_object <- import_data(
  response_matrix = highmoi_example_data$response_matrix,
  grna_matrix = highmoi_example_data$grna_matrix,
  grna_target_data_frame = grna_target_data_frame_highmoi,
  moi = "high",
  extra_covariates = highmoi_example_data$extra_covariates,
  response_names = highmoi_example_data$gene_names
)

# set analysis parameters, assign grnas, run qc, run calibration check
sceptre_object <- sceptre_object |>
  set_analysis_parameters(
    side = "left",
    resampling_mechanism = "permutations"
  ) |>
  assign_grnas(method = "thresholding") |>
  run_qc() |>
  run_calibration_check(
    n_calibration_pairs = 500,
    calibration_group_size = 2
  )
#> Note: If you are on a Mac laptop or desktop, consider setting `parallel = TRUE` to improve speed. Otherwise, keep `parallel = FALSE`.
#> Constructing negative control pairs.
#>  ✓
#> Generating permutation resamples.
#>  ✓
#> Analyzing pairs containing response ENSG00000253631 (1 of 96)
#> Analyzing pairs containing response ENSG00000100053 (5 of 96)
#> Analyzing pairs containing response ENSG00000100325 (10 of 96)
#> Analyzing pairs containing response ENSG00000253963 (15 of 96)
#> Analyzing pairs containing response ENSG00000100314 (20 of 96)
#> Analyzing pairs containing response ENSG00000177993 (25 of 96)
#> Analyzing pairs containing response ENSG00000099956 (30 of 96)
#> Analyzing pairs containing response ENSG00000253920 (35 of 96)
#> Analyzing pairs containing response ENSG00000203280 (40 of 96)
#> Analyzing pairs containing response ENSG00000187792 (45 of 96)
#> Analyzing pairs containing response ENSG00000211666 (50 of 96)
#> Analyzing pairs containing response ENSG00000236611 (55 of 96)
#> Analyzing pairs containing response ENSG00000253546 (60 of 96)
#> Analyzing pairs containing response ENSG00000099917 (65 of 96)
#> Analyzing pairs containing response ENSG00000253889 (70 of 96)
#> Analyzing pairs containing response ENSG00000099889 (75 of 96)
#> Analyzing pairs containing response ENSG00000241973 (80 of 96)
#> Analyzing pairs containing response ENSG00000225783 (85 of 96)
#> Analyzing pairs containing response ENSG00000279548 (90 of 96)
#> Analyzing pairs containing response ENSG00000100068 (95 of 96)