Runs cTWAS fine-mapping for regions without LD (L = 1)
Source:R/ctwas_finemapping.R
finemap_regions_noLD.RdRuns cTWAS fine-mapping for regions without LD (L = 1)
Usage
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 fine-mapping results.
- include_prior
If TRUE, include priors in fine-mapping results.
- include_mu2
If TRUE, include estimated effect size variance (mu2) in fine-mapping results.
- include_susie_alpha
If TRUE, include susie alpha matrix from fine-mapping results.
- include_susie_result
If TRUE, include the "susie" result object in fine-mapping 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.