LDAK-KVIK options
Default parameters in LDAK-KVIK can be modified by adding options to the command line. Below, we present a list of options for each step.
Step 1
Argument |
Description |
--kvik-step1 |
Name of the output files of the step 1 |
--bfile |
Name of the .bed file to be analyzed |
--bgen |
Name of the .bgen file to be analyzed |
--sample |
Name of the .sample file corresponding to the .bgen file |
--pheno |
Name of the phenotype file |
--covar |
Name of the quantitative covariate file |
--covar-numbers |
Specify a subset of covariates by number. For example, --covar-numbers 1,2,4-6,8 |
--covar-names |
Specify a subset of covariates by names. For example, --covar-names PC1,PC3,age |
--factor |
Name of the categorical covariate file |
--max-threads |
Number of threads (used for parallel computing) |
--binary YES |
Indicates that the analysed phenotype is binary |
--num-pedigree-predictors |
The number of SNPs used when testing for structure (default: 512) |
–-check-pedigree NO |
Indicates that there will be no check for structure. In this case, it is assumed that there is structure |
-–num-MCMC |
Number of random vectors used to compute the heritability estimate in randomized Haseman-Elston regression (default: ten if \(n\) < 40000, three if \(n\) > 40000) |
-–num-divide |
Number of partitions used to compute the heritability estimate in randomized Haseman-Elston regression (default: 40) |
-–num-scans |
Number of scans performed by the Variational Bayes algorithm to construct PRS |
-–cv-proportion |
Proportion of individuals used to determine elastic net hyperparameters |
-–tolerance |
This number is multiplied by \(n\), and specifies the threshold for convergence for the likelihood in the Variational Bayes algorithm (default: \(10^{-6}\)) |
–-num-calibration-predictors |
Number of SNPs used to compute the Grammar-Gamma scaling factor (default: 20) |
Step 2
Please note that the arguments must match those used in Step 1 (i.e., you must use the same output filename, provide the same data and phenotype files, and if you used covariates in Step 1, you must also use them in Step 2).
Argument |
Description |
--kvik-step2 |
Name of the output files of Step 2. Note that this should have the same name as Step 1. |
--bfile |
Name of the .bed file to be analyzed |
--bgen |
Name of the .bgen file to be analyzed |
--sample |
Name of the .sample file corresponding to the .bgen file |
--pheno |
Name of the phenotype file |
--covar |
Name of the quantitative covariate file |
--covar-numbers |
Specify a subset of covariates by number. For example, --covar-numbers 1,2,4-6,8 |
--covar-names |
Specify a subset of covariates by names. For example, --covar-numbers PC1,PC3,age |
--factor |
Name of the categorical covariate file |
--max-threads |
Number of threads (used for parallel computing) |
–-spa-test NO |
Indicates that no saddlepoint approximation will be used when testing binary phenotypes |
Step 3
Argument |
Description |
--kvik-step3 |
Name of the output files of Step 3. Note that this should have the same name as Step 1 and Step 2. |
--bfile |
Name of the .bed file to be analyzed |
--genefile |
Name of the gene annotation file. Instructions for downloading this can be found on the input page |
--max-threads |
Number of threads (used for parallel computing) |