Description Usage Arguments Value Examples
This function runs the BLUP|GA method where SNPs in candidate genes are weighted in the GRM prior to GBLUP
1 | blupga_CAND(G, phenodata, valset, GRMs = NULL, verbose = T)
|
G |
G-matrix constructed using all available SNPs and samples Defaults to NULL. |
valset |
vector of indices that defines which rows in |
GRMs |
List of G-matrices, each constructed from just the SNPs in one candidate gene/region. Defaults to NULL. |
@param |
phenodata data frame with 2 or 3 columns. One col must be named 'ID' and contain sample IDs. Another col must be named 'y' and contain the phenotypes. If fixed effects are included then a 3rd col called 'FE' should contain the categorical effects. Defaults to NULL. |
A data frame containing the correlation between the predicted phenotype and the true phenotype of the individuals in the valset
.
Since BLUP|GA is run for each value of omega (W) from 0.0 to 1.0 in increments of 0.10, each row of the returned data frame contains the cross-validation correlation at one value of omega (W). This allows the user to find the value of W at which the predictive ability (COR) is maximised.
omega weighting for selected SNPS in candidate genes (0.0–1.0)
cross validation predictive ability (0.0–1.0)
1 |
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