Compute SuSiE-inf TWAS weights — susie_inf

Extracts coefficients from an existing SuSiE-inf fit or fits `susieR::susie()` with `unmappable_effects = "inf"`.

Usage

susie_inf_weights(
  X = NULL,
  y = NULL,
  susie_inf_fit = NULL,
  retain_fit = FALSE,
  ...
)

Arguments

X: Genotype matrix. Required when `susie_inf_fit` is NULL.
y: Phenotype vector. Required when `susie_inf_fit` is NULL.
susie_inf_fit: Optional fitted SuSiE-inf object.
retain_fit: If TRUE, stores the fitted object as an attribute on the returned weights.
...: Additional arguments passed to `susieR::susie()` when fitting.

Value

Numeric vector of variant weights.

Non-zero weights with zero PIPs

SuSiE-inf decomposes effects into a mappable component (driven by `alpha * mu`, reported as per-variant PIPs) and an infinitesimal component (driven by `theta`). When the fit converges with no mappable effects – all `V` and `mu` zero, so every `pip == 0` – the returned weights are still non-zero because `susieR::coef.susie` adds `theta / X_column_scale_factors` to the mappable coefficient. This is intentional: it captures diffuse polygenic signal that the mappable component could not localize to any credible set. Consumers that interpret per-variant PIPs as a gate on whether to use the weights should be aware that low or zero PIPs do not imply zero TWAS weights here.