Compute p-values for each target_id

Usage

compute_p_values(
  cpo,
  subset = NULL,
  p_adj_method = "BH",
  gam_method = "REML",
  gam_optimizer = "efs",
  silent = TRUE
)

Arguments

cpo: a cpam object
subset: a character vector of target_id names
p_adj_method: method for p-value adjustment
gam_method: fitting method for mgcv::gam (default is "REML")
gam_optimizer: optimization method for mgcv::gam (default is "efs")
silent: logical; silences warnings from model fitting (default is TRUE)

Value

an updated cpam object with raw, adjusted, and possibly aggregated p-values stored in the new slot "p_table"

Details

This function computes p-values for each target_id in the supplied cpam object. The p-values are computed from a negative binomial GAM model with a thin-plate spline basis function(s) for time using the mgcv package.

The p-values are stored in the new slot p_table in the cpam object. If aggregate_to_gene is set to TRUE (default), the target p-values are aggregated to the gene level using the lancaster method. The columns p_val_target and p_val_gene store the raw p-values for target- and gene-level, respectively. The function also computes adjusted p-values using the p_adj_method. The default method is "BH" (Benjamini-Hochberg), but any methods supported by the function p.adjust can be used. The adjusted p-values are stored in the columns q_val_target and q_val_gene.

References

Wood, S.N. (2013a) On p-values for smooth components of an extended generalized additive model. Biometrika 100:221-228 doi:10.1093/biomet/ass048