### Options

Note: The power calculation requires the true SNP-heritability, so that the power is the probability of estimating a SNP-heritability that is greater than zero.

Note: The default value 2e-5 is obtained from the genetic relatedness between unrelated individuals using genome-wide common SNPs, which is basically the variance of the off-diagonal elements of the GRM. If your GRM is constructed from selected SNPs and/or uses differential weighting of SNPs, you can specify this by the empirical variance of the off-diagonals of the GRM.

### Results

Standard error (SE): Standard error of the SNP-heritability ($$h^2$$).

NCP: Non-centrality paramter of the chi-squared test statistic, which equal to $$h^4 / (SE)^2$$.

Power: The probability of detecting $$h^2 > 0$$ for the given the user-specified type I error rate and the SNP-heritability assumed in the population.

### Options

Note: The power calculation requires the true SNP-heritability, so that the power is the probability of estimating a SNP-heritability that is greater than zero.

Note: The default value 2e-5 is obtained from the genetic relatedness between unrelated individuals using genome-wide common SNPs, which is basically the variance of the off-diagonal elements of the GRM. If your GRM is constructed from selected SNPs and/or uses differential weighting of SNPs, you can specify this by the empirical variance of the off-diagonals of the GRM.

### Outputs

Standard error (SE): Standard error of the SNP-heritability ($$h^2$$).

NCP: Non-centrality paramter of the chi-squared test statistic, which equal to $$h^4 / (SE)^2$$.

Power: The probability of detecting $$h^2 > 0$$ for the given the user-specified type I error rate and the SNP-heritability assumed in the population.

### Options

#### Trait #1

Note: The calculation of the SE of $$r_G$$ requires the true SNP-heritability of the trait.

#### Trait #2

Note: The calculation of the SE of $$r_G$$ requires the true SNP-heritability of the trait.

#### Other details

Note: The default value 2e-5 is obtained from the genetic relatedness between unrelated individuals using genome-wide common SNPs, which is basically the variance of the off-diagonal elements of the GRM. If your GRM is constructed from selected SNPs and/or uses differential weighting of SNPs, you can specify this by the empirical variance of the off-diagonals of the GRM.

### Outputs

Standard error (SE): Standard error of the genetic correlation ($$r_G$$).

NCP: Non-centrality paramter of the chi-squared test statistic, which equals to $$r_G^2 / (SE)^2$$.

Power: The probability of detecting $$r_G$$ for the given user-specified type I error rate, SNP-heritability, and genetic correlation assumed in the population.

### Inputs

#### Other details

Note: Here we assume that the genetic and phenotypic correlation is the same

### Options

#### Trait #1

Note: The calculation of the SE of $$r_G$$ requires the true SNP-heritability of the disease.

#### Trait #2

Note: The calculation of the SE of $$r_G$$ requires the true SNP-heritability of the disease.

#### Other details

Note: The default value 2e-5 is obtained from the genetic relatedness between unrelated individuals using genome-wide common SNPs, which is basically the variance of the off-diagonal elements of the GRM. If your GRM is constructed from selected SNPs and/or uses differential weighting of SNPs, you can specify this by the empirical variance of the off-diagonals of the GRM.

### Outputs

Standard error (SE): Standard error of the genetic correlation ($$r_G$$).

NCP: Non-centrality paramter of the chi-squared test statistic, which equals to $$r_G^2 / (SE)^2$$.

Power: The probability of detecting $$r_G$$ for the given user-specified type I error rate, SNP-heritability, and genetic correlation assumed in the population.

### Inputs

#### Other details

Note: Here we assume that the genetic and phenotypic correlation is the same

### Options

#### Quantitative trait

Note: The calculation of the SE of $$r_G$$ requires the true SNP-heritability of the trait.

#### Case-control study

Note: The calculation of the SE of $$r_G$$ requires the true SNP-heritability of the disease.

#### Other details

Note: The default value 2e-5 is obtained from the genetic relatedness between unrelated individuals using genome-wide common SNPs, which is basically the variance of the off-diagonal elements of the GRM. If your GRM is constructed from selected SNPs and/or uses differential weighting of SNPs, you can specify this by the empirical variance of the off-diagonals of the GRM.

### Outputs

Standard error (SE): Standard error of the genetic correlation ($$r_G$$).

NCP: Non-centrality paramter of the chi-squared test statistic, which equals to $$r_G^2 / (SE)^2$$.

Power: The probability of detecting $$r_G$$ for the given user-specified type I error rate, SNP-heritability, and genetic correlation assumed in the population.