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Set analysis parameters

Source: R/s4_analysis_functs_1.R
set_analysis_parameters.Rd

set_analysis_parameters() sets the analysis parameters that control how the statistical analysis is to be conducted. See Chapter 2 of the manual for more detailed information about this function.

Usage

set_analysis_parameters(
  sceptre_object,
  discovery_pairs = data.frame(grna_target = character(0), response_id = character(0)),
  positive_control_pairs = data.frame(grna_target = character(0), response_id =
    character(0)),
  side = "both",
  grna_integration_strategy = "union",
  formula_object = "default",
  resampling_approximation = "skew_normal",
  control_group = "default",
  resampling_mechanism = "default",
  multiple_testing_method = "BH",
  multiple_testing_alpha = 0.1
)

Arguments

sceptre_object

a sceptre_object

discovery_pairs

(optional) a data frame with columns grna_target and response_id specifying the discovery pairs to analyze

positive_control_pairs

(optional) a data frame with columns grna_target and response_id specifying the positive control pairs to analyze

side

(optional; default "both") the sidedness of the test, one of "left", "right", or "both"

grna_integration_strategy

(optional; default "union") a string specifying the gRNA integration strategy, either "singleton", "union", or "bonferroni"

formula_object

(optional) a formula object specifying how to adjust for the covariates in the model

resampling_approximation

(optional; default "skew_normal") a string indicating the resampling approximation to make to the null distribution of test statistics, either "skew_normal" or "no_approximation"

control_group

(optional) a string specifying the control group to use in the differential expression analysis, either "complement" or "nt_cells"

resampling_mechanism

(optional) a string specifying the resampling mechanism to use, either "permutations" or "crt"

multiple_testing_method

(optional; default "BH") a string specifying the multiple testing correction method to use; see p.adjust.methods for options

multiple_testing_alpha

(optional; default 0.1) a numeric specifying the nominal level of the multiple testing correction method

Value

an updated sceptre_object in which the analysis parameters have been set

Note

Every argument to this function is optional, but typically, users want to specify discovery_pairs at minimum.

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
positive_control_pairs <- construct_positive_control_pairs(sceptre_object)
discovery_pairs <- construct_cis_pairs(sceptre_object,
  positive_control_pairs = positive_control_pairs,
  distance_threshold = 5e6
)
sceptre_object <- sceptre_object |>
  set_analysis_parameters(
    discovery_pairs = discovery_pairs,
    positive_control_pairs = positive_control_pairs,
    side = "left"
  )