Usage Arguments Value Author(s) Examples
1 | gskat_seq_opt(y, XC, Z, ID, NB=10000, impute.method = "fixed", SNP.weights = NULL, w_a = 1, w_b = 25, resampling = TRUE, pw = "Rade", Uc = TRUE, sW = FALSE, np = 10000)
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y |
binary phenotype coded as 0, 1 |
XC |
covaraite matrix, not including the intercept column |
Z |
SNP genotypes coded 0/1/2 (minor allele count). |
ID |
Pedigree ID matrix, including Family ID (FID) and Individual ID (IID) |
NB |
number of comparisons to get p-value, default=10000 |
impute.method |
default is fixed method i.e. fill with means |
SNP.weights |
If NULL, the default beta (1,25) desensity will be used, or a custimoized weight vector may be used |
w_a |
The first parameter of the beta density in the weight function |
w_b |
The second parameter of the beta density in the weight function |
resampling |
If TRUE, resampling will be applied |
pw |
r.v. used in the perturbation, "Norm"=Normal , "Rade"=Rademacher |
Uc |
Score centered or not |
sW |
standardize weights |
np |
number of perturbed samples. default=10000 |
pfinal |
Returns p-value |
Xuefeng Wang
1 2 | attach(gdata)
gskat_seq_opt(y,X[,-1],Z,ID=data.frame(FID=ID$FID,IID=ID$IID),NB=10000)
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