Extracts coefficients from an existing single-effect fit, as produced by
fineMappingPipeline(..., methods = "ser") on summary statistics.
The SER model carries the same alpha / mu /
X_column_scale_factors structure as a SuSiE fit — with a single
effect, so alpha has one row — so extraction is identical.
Usage
serWeights(
X = NULL,
y = NULL,
serFit = NULL,
fitRetention = c("none", "slim", "full")
)Arguments
- X
Optional genotype matrix; when supplied it is only used to check that the fit covers the same number of variants.
- y
Unused; retained for signature compatibility.
- serFit
Optional fitted SER object.
- fitRetention
How much of the fit is kept on the returned weights:
"none"attaches nothing,"slim"and"full"attach it as the"fit"attribute. These extractors hold no trimmable intermediates, so the two retaining levels behave alike here.
Details
SER fits only exist on the summary-statistics path, because
susieR::susie_ser is the only implementation
fineMappingPipeline has for the "ser" method. That
does not restrict the weights: a fit is a fit, and weights read off an
RSS fit are as usable for TWAS as any from penalized regression.
Examples
data(eqtlRegionExample)
X <- eqtlRegionExample$X[, 1:30]
y <- eqtlRegionExample$yRes
z <- apply(X, 2, function(g) summary(stats::lm(y ~ g))$coefficients[2, 3])
fit <- suppressWarnings(susieR::susie_ser(z = z, n = nrow(X)))
#> HINT: susie_ser() uses a one-effect credible-set model as in Maller et al. 2012. Because no LD reference is supplied, credible sets are reported without purity filtering; susie_ser() applies the attainable-coverage filter from SparsePro (Zhang et al. 2023). Set coverage = NULL to skip CS construction and silence this hint, or call susie_get_cs(fit, Xcorr = R, ...) afterward to apply a purity filter.
serWeights(serFit = fit)
#> chr22:32119788:T:C chr22:32119867:T:G chr22:32119961:T:G chr22:32120053:T:C
#> 0 0 0 0
#> chr22:32120593:A:G chr22:32120636:T:C chr22:32120932:G:A chr22:32120975:A:G
#> 0 0 0 0
#> chr22:32121290:C:T chr22:32121498:A:C chr22:32121635:T:G chr22:32121702:A:G
#> 0 0 0 0
#> chr22:32121936:G:A chr22:32122351:A:G chr22:32122676:A:G chr22:32123055:A:G
#> 0 0 0 0
#> chr22:32123164:T:C chr22:32123383:T:C chr22:32123461:T:C chr22:32123806:C:T
#> 0 0 0 0
#> chr22:32124049:G:A chr22:32124126:C:T chr22:32124147:A:C chr22:32124381:G:A
#> 0 0 0 0
#> chr22:32124644:A:G chr22:32124683:T:C chr22:32124952:C:A chr22:32125308:A:G
#> 0 0 0 0
#> chr22:32125638:A:C chr22:32125730:G:A
#> 0 0