View source: R/theoretical_gwas.R
generate_gwas_ss | R Documentation |
After generating the set of causal effects at each SNP, use an LD correlation matrix to transform the effects to reflect the correlation structure at the SNPs. Note if running many repeats, only need to generate the LD-modified params once and then can repeatedly re-sample using generate_gwas_ss
generate_gwas_ss(
params,
nid,
vy = 1,
minmaf = 0.001,
ld = NULL,
ldobj = NULL,
ldobjlist = NULL,
ldobjfiles = NULL,
ldobjdir = NULL,
gwasglue2 = FALSE,
nthreads = 1
)
params |
Output from |
nid |
sample size |
vy |
Variance of trait |
minmaf |
minimum allowed maf. default=0.01 to prevent instability |
ld |
LD correlation matrix. Must be same dimension as params |
ldobj |
LD objects (e.g. see test_ldobj) |
ldobjlist |
List of LD objects |
ldobjfiles |
Array of filenames containing LD object files (e.g. see |
ldobjdir |
Directory containing output from |
gwasglue2 |
Logical, creates a gwasglue2 SummarySet when @param ldobj is not NULL (default FALSE). |
nthreads |
Number of threads (can be slow for complete GWAS and large LD regions) |
Updated params
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