Add interactions to a trajectory model

This function adds significant interactions to a given trajectory model if they do not already exist. It identifies significant interactions based on the provided threshold and updates the model features with logistic features derived from these interactions. The trajectory model is then re-learned with the new features.

Usage

add_interactions(
  traj_model,
  interaction_threshold = 0.001,
  max_motif_n = NULL,
  max_add_n = NULL,
  max_n = NULL,
  lambda = 0.00001,
  alpha = 1,
  seed = 60427,
  interactions = NULL,
  ignore_feats = c("TT", "CT", "GT", "AT", "TC", "CC", "GC", "AC", "TG", "CG", "GG",
    "AG", "TA", "CA", "GA", "AA")
)

Arguments

interaction_threshold

threshold for the selecting features to create interactions. IQ learns a linear model on the features and selects the features with coefficients above this threshold. Default: 0.001

max_motif_n

maximum number of motifs to consider for interactions. If NULL, all motifs above the interaction_threshold will be considered. Default: NULL

max_add_n

maximum number of additional features to consider for interactions. If NULL, all additional features above the interaction_threshold will be considered. Default: NULL

max_n

maximum number of interactions to consider. If NULL, all interactions will be considered. If set, the interactions will be selected based on correlation with the signal in the training data. Default: NULL

seed

random seed for reproducibility.

interactions

A precomputed interaction matrix. If provided, the function will not compute the interactions. Default: NULL

ignore_feats

A character vector of features to ignore when creating interactions. Default: dinucleotides

Value

The updated trajectory model with added interactions.