model.gof {lfa} | R Documentation |
Compute SNP-by-SNP goodness-of-fit when compared to population structure. This can be aggregated to determine genome-wide goodness-of-fit for a particular value of d.
model.gof(X, LF, B)
X |
a matrix of SNP genotypes, i.e. an integer matrix of 0's, 1's, and 2's. Sparse matrices of class Matrix are not supported (yet). |
LF |
matrix of logistic factors |
B |
number of null datasets to generate - B=1 is usualy sufficient. If computational time/power allows, a few extra B could be helpful |
This function returns p-values for LFA model goodness of fit based on a simulated null.
vector of p-values for each SNP.
Genotype matrix is expected to be a matrix of integers with values 0, 1, and 2. Currently no support for missing values. Note that the coding of the SNPs does not affect the algorithm.
LF <- lfa(hgdp_subset, 4) gof_4 <- model.gof(hgdp_subset, LF, 3) LF <- lfa(hgdp_subset, 10) gof_10 <- model.gof(hgdp_subset, LF, 3) hist(gof_4) hist(gof_10)