Runs cTWAS fine-mapping for regions without LD (L = 1)

finemap_regions_noLD(
  region_data,
  group_prior = NULL,
  group_prior_var = NULL,
  min_var = 2,
  min_gene = 1,
  null_method = c("ctwas", "susie", "none"),
  coverage = 0.95,
  include_cs = TRUE,
  include_prior = FALSE,
  include_mu2 = FALSE,
  include_susie_alpha = TRUE,
  include_susie_result = FALSE,
  snps_only = FALSE,
  ncore = 1,
  verbose = FALSE,
  logfile = NULL,
  ...
)

Arguments

region_data: region_data to be finemapped
group_prior: a vector of prior inclusion probabilities for different groups. If NULL, it will use uniform prior inclusion probabilities.
group_prior_var: a vector of prior variances for different groups. If NULL, it will set prior variance = 50 as the default in susie_rss.
min_var: minimum number of variables (SNPs and genes) in a region.
min_gene: minimum number of genes in a region.
null_method: Method to compute null model, options: "ctwas", "susie" or "none".
coverage: A number between 0 and 1 specifying the “coverage” of the estimated confidence sets
include_cs: If TRUE, include credible sets (CS) to finemapping results.
include_prior: If TRUE, include priors in finemapping results.
include_mu2: If TRUE, include estimated effect size variance (mu2) in finemapping results.
include_susie_alpha: If TRUE, include susie alpha matrix from finemapping results.
include_susie_result: If TRUE, include the "susie" result object in finemapping results.
snps_only: If TRUE, use only SNPs in the region data.
ncore: The number of cores used to parallelize computation over regions
verbose: If TRUE, print detail messages
logfile: the log file, if NULL will print log info on screen
...: Additional arguments of susie_rss.

Value

a list with cTWAS finemapping results.