Calculates p-values and adjusted q-values for a given effect in a specific cell type.
Usage
compute_significance(
input_list,
cell_type,
effect_name,
beta_name = "beta_estimate",
standard_error_name = "standard_error_matrix",
sided = 2,
direction = "pos"
)Arguments
- input_list
A list of model outputs with beta and standard error matrices.
- cell_type
Character. Cell type of interest.
- effect_name
Character. Name of the covariate/effect of interest.
- beta_name
Name of the beta matrix (default: "beta_estimate").
- standard_error_name
Name of the standard error matrix (default: "standard_error_matrix").
- sided
Integer. 1 for one-sided, 2 for two-sided test.
- direction
Character. "pos" or "neg", used if
sided = 1.