Runs cTWAS post-processing procedure for region merging without LD

postprocess_region_merging_noLD(
  region_info,
  region_data,
  z_snp,
  z_gene,
  weights,
  snp_map,
  finemap_res,
  susie_alpha_res,
  combine_PIPs = TRUE,
  mapping_table = NULL,
  group_prior = NULL,
  group_prior_var = NULL,
  pip_thresh = 0.5,
  filter_cs = FALSE,
  maxSNP = Inf,
  ncore = 1,
  verbose = FALSE,
  logfile = NULL,
  ...
)

Arguments

region_info: a data frame of region definitions.
region_data: region_data to be fine-mapped.
z_snp: A data frame with columns: "id", "z", giving the z-scores for SNPs.
z_gene: A data frame with columns: "id", "z", giving the z-scores for genes.
weights: a list of preprocessed weights.
snp_map: a list of data frames with SNP-to-region map for the reference.
finemap_res: a data frame of original finemapping result.
susie_alpha_res: a data frame of original susie alpha result.
combine_PIPs: if TRUE, select boundary genes after combining gene PIPs.
mapping_table: a data frame of mapping between molecular traits and genes, with required columns: "molecular_id", "gene_name".
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.
pip_thresh: PIP cutoff for selecting boundary genes to merge regions.
filter_cs: If TRUE, only select boundary genes in credible sets for region merge.
maxSNP: Inf or integer. Maximum number of SNPs in a region. Default is Inf, no limit. This can be useful if there are many SNPs in a region and you don't have enough memory to run the program.
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 finemap_regions.

Value

a list with region merge results.