Extract Top Contributing Features for Factors — extract_top_factor

Identifies the most influential features for specified factors using MOFA+ or MCIA integration results. Features are selected based on either a percentile cutoff or an absolute loading threshold.

Usage

extract_top_factor_features(
  expomicset,
  factors = NULL,
  pval_col = "p_adjust",
  pval_thresh = 0.05,
  method = "percentile",
  percentile = 0.9,
  threshold = 0.3,
  action = "add"
)

Arguments

expomicset: A MultiAssayExperiment object containing integration results.
factors: A character vector specifying the factors of interest.
method: A character string specifying the feature selection method ("percentile" or "threshold"). Default is "percentile".
percentile: A numeric value between 0 and 1 indicating the percentile threshold for feature selection when method = "percentile". Default is 0.9.
threshold: A numeric value specifying the absolute loading cutoff for feature selection when method = "threshold". Default is 0.3.
action: A character string indicating whether to return results ("get") or add them to metadata ("add"). Default is "add".

Value

If action = "add", returns the modified expomicset with selected features stored in metadata. If action = "get", returns a data frame containing:

feature: The selected feature contributing to the factor.
factor: The factor to which the feature contributes.
loading: The factor loading value of the feature.
exp_name: The experiment from which the feature originated.

Details

The function extracts factor loadings from metadata(expomicset), applies filtering based on the selected method, and identifies top contributing features for each specified factor. Features can be selected using:

Percentile-based filtering (method = "percentile"): Selects features with absolute loadings above a specified percentile.
Threshold-based filtering (method = "threshold"): Selects features with absolute loadings exceeding a fixed value.

Examples

if (FALSE) { # \dontrun{
results <- extract_top_factor_features(
  expomicset = expom,
  factors = c("Factor1", "Factor2"),
  method = "percentile",
  percentile = 0.9,
  action = "get"
)
} # }