model.gof: LFA model goodness of fit
In lfa: Logistic Factor Analysis for Categorical Data

Description Usage Arguments Details Value Note Examples

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.

1	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)