Runs cTWAS fine-mapping for regions
finemap_regions(
region_data,
LD_map,
weights,
L = 5,
group_prior = NULL,
group_prior_var = NULL,
use_null_weight = TRUE,
coverage = 0.95,
min_abs_corr = 0.1,
include_cs = TRUE,
get_susie_alpha = TRUE,
snps_only = FALSE,
force_compute_cor = FALSE,
save_cor = FALSE,
cor_dir = NULL,
LD_format = c("rds", "rdata", "mtx", "csv", "txt", "custom"),
LD_loader_fun = NULL,
snpinfo_loader_fun = NULL,
ncore = 1,
verbose = FALSE,
logfile = NULL,
...
)
region_data to be finemapped
a data frame with filenames of LD matrices for the regions.
a list of preprocessed weights.
the number of effects or a vector of number of effects for each region.
a vector of two prior inclusion probabilities for SNPs and genes. If NULL, it will use uniform prior inclusion probabilities.
a vector of two prior variances for SNPs and gene effects.
If NULL, it will set prior variance = 50 as the default in susie_rss
.
If TRUE, allow for a probability of no effect in susie
A number between 0 and 1 specifying the “coverage” of the estimated confidence sets
Minimum absolute correlation allowed in a credible set.
If TRUE, add credible sets (CS) to finemapping results.
If TRUE, get susie alpha matrix from finemapping results.
If TRUE, use only SNPs in the region data.
If TRUE, force computing correlation (R) matrices
If TRUE, save correlation (R) matrices to cor_dir
a string, the directory to store correlation (R) matrices
file format for LD matrix. If "custom", use a user defined
LD_loader_fun()
function to load LD matrix.
a user defined function to load LD matrix when LD_format = "custom"
.
a user defined function to load SNP information file, if SNP information files are not in standard cTWAS reference format.
The number of cores used to parallelize computation over regions
If TRUE, print detail messages
the log file, if NULL will print log info on screen
Additional arguments of susie_rss
.
a data frame of cTWAS finemapping results.