#################
# Test mpp_proc #
#################
context("Test mpp_proc")
library(testthat)
library(mppR)
# references values (taken on the USNAM example - 24/05/2019)
# Reference QTL effects
QTL_cr <- c(2.6841679, 5.5525152, 0.6753642, 2.3775748, 4.0971491)
QTL_par <- c(0.0000000, -5.5525152, -2.6841679, -0.6753642, -4.0971491,
-2.3775748)
QTL_anc <- c(0.000000, -1.626181, -1.626181, -3.201762, -3.201762,
-5.552515)
QTL_biall <- c(5.207004, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000)
Ref_QTL <- list(QTL_cr, QTL_par, QTL_anc, QTL_biall)
data(mppData)
Qeff <- c('cr', 'par', 'anc', 'biall')
for(i in 1:4){
res <- mpp_proc(pop.name = "USNAM", trait.name = "ULA",
mppData = mppData, Q.eff = Qeff[i],
plot.gen.eff = FALSE, CI = FALSE,
output.loc = tempdir(), verbose = FALSE)
test_i <- paste('Q.eff =', Qeff[i])
test_that(test_i, {
expect_equal(object = res$QTL.effects$Qeff$Q1$Effect,
expected = Ref_QTL[[i]], tolerance = .0001)
})
}
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