Orchestrator that runs all bias-audit diagnostics on a model + data bundle and returns a structured report. Intended to be emitted as a first-class output of every OmicSelector biomarker analysis.
Usage
os_bias_audit(
X,
y,
cohort,
predictions = NULL,
covariates = NULL,
specimen_id = NULL,
sample_id = NULL,
feature_names = NULL,
seed = 42L
)Arguments
- X
Feature matrix (n x p).
- y
Binary outcome.
- cohort
Cohort/dataset identity per sample.
- predictions
Optional numeric vector of model predictions (n).
- covariates
Optional named list of numeric or factor covariates (e.g., list(age = age_years, sex = sex_factor)).
- specimen_id
Optional specimen-level IDs for duplicate detection.
- sample_id
Optional sample-level IDs used when reporting duplicate pairs. If omitted, row names of
Xare used when available.- feature_names
Optional feature labels.
- seed
Random seed.