run susie_rss storing some additional information for coloc
runsusie(
d,
suffix = 1,
maxit = 100,
repeat_until_convergence = TRUE,
s_init = NULL,
...
)coloc dataset, must include LD (signed correlation matrix) and N (sample size)
suffix label that will be printed with any error messages
maximum number of iterations for the first run of susie_rss(). If susie_rss() does not report convergence, runs will be extended assuming repeat_until_convergence=TRUE. Most users will not need to change this default.
keep running until susie_rss() indicates convergence. Default TRUE. If FALSE, susie_rss() will run with maxit iterations, and if not converged, runsusie() will error. Most users will not need to change this default.
used internally to extend runs that haven't converged. don't use.
arguments passed to susie_rss. In particular, if you want to match some coloc defaults, set
prior_variance=0.2^2 (if a case-control trait) or (0.15/sd(Y))^2 if a quantitative trait
estimate_prior_variance=FALSE
otherwise susie_rss will estimate the prior variance itself
results of a susie_rss run, with some added dimnames
library(coloc)
data(coloc_test_data)
result=runsusie(coloc_test_data$D1)
#> running max iterations: 100
#> converged: TRUE
summary(result)
#>
#> Variables in credible sets:
#>
#> variable variable_prob cs
#> 105 0.9593968 1
#>
#> Credible sets summary:
#>
#> cs cs_log10bf cs_avg_r2 cs_min_r2 variable
#> 1 10.2121 1 1 105