This online calculator can calculate additive genetic contribution and genetic association for quantitative traits collected and/or derived from HCP dataset. Please organize your data file in a comma separated value format. If you use Mac, please ensure that the file is saved in MS Windows CSV format. Otherwise, the file may be missing line separators.
The file should include the compulsory
ID column with HCP ids. The order of column can be random. The file may include up to 256 columns or traits and or covariates. The traits and covariates are interchangeable. Please do not label any of the columns
gender because this constitutes publically identifiable information. The calculator provides an option to merge your file with sex information internally. Alternatively you can code this information using another name such as COV1. You can download the example file here. You can download pedigrees here.
There are four choice of pedigree that serves as the basis for heritability calculations. The self-reported pedigree is based on the self-declared relatedness that was verified using genetic panel. The other three pedigrees were derived empirically from the genetic panel data. The Kinship-based INference for Genome wide association study (KING) method was developed to approximate self-reported CR values 1. The weighted allelic correlation approach weights relatedness values by minor allelic frequency (MAF) using a weighting parameter (α), that can take values of 1, 0 or -1 2,3.
The WAC weighting of α=1 calculates relatedness based on common variants. WAC weighting of α=-1 calculates relatedness weighted towards sharing of low MAF variants. Weighting of α=0 calculates CR values that are independent of the MAF.
Heritability calculations are performed using Fast Permutation Heritability Inference (FPHI) approach (solar-eclipse: polygenic -fphi command). It uses a single step estimation to produce an asymptotically unbiased estimate 4. The FPHI provides a significant (103) computational acceleration relative to the standard iterative maximum likelihood estimation in SOLAR-Eclipse.