tibbles <- list()
data <- tidyr::expand_grid(
n_individuals = c(10, 100, 1000),
n_phenotypes = c(1, 10, 100),
n_snps_per_phenotype = c(1, 10, 100, 1000)
)
for (i in seq_len(nrow(data))) {
message(Sys.time(), ": ", i, "/" ,nrow(data))
t <- plinkr::compare_assoc_qt_speed(
n_individuals = data$n_individuals[i],
n_phenotypes = data$n_phenotypes[i],
n_snps_per_phenotype = data$n_snps_per_phenotype[i]
)
# fastest_row_index <- which.min(t$time_sec)
# t_best <- t[fastest_row_index, ]
t_best <- t
t_best$n_invididuals <- data$n_individuals[i]
t_best$n_phenotypes <- data$n_phenotypes[i]
t_best$n_snps_per_phenotype <- data$n_snps_per_phenotype[i]
tibbles[[i]] <- t_best
}
t <- dplyr::bind_rows(tibbles)
t
readr::write_csv(t, "speed_comparison.csv")
if (1 == 2) {
# There are hints that PLINK v1.7 cannot handle this
t <- plinkr::compare_assoc_qt_speed(
n_individuals = 1000,
n_phenotypes = 100,
n_snps_per_phenotype = 1000,
plink_optionses = list(plinkr::create_plink_v1_7_options()),
verbose = TRUE
)
}
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