# prepare environment
source(snakemake@params$setup_code_fname)
devtools::load_all("../..")
# run model
fit <- pareg::pareg(
study$df %>%
select(gene, pvalue) %>%
mutate(pvalue = -ifelse(
pvalue > 0,
log10(pvalue),
log10(min(pvalue[pvalue > 0]))
)),
df_terms,
term_network = term_similarities_sub,
cv = TRUE,
cv_method = pareg_cv_method,
family = pareg::gaussian,
lasso_param_range = lasso_param_range,
network_param_range = network_param_range,
tempdir = file.path(dirname(snakemake@output$fname), "cv_dump"),
max_iteration = pareg_max_iteration
)
df <- fit %>%
as.data.frame() %>%
mutate(method = "pareg_gaussian", enrichment = abs(enrichment))
df %>%
arrange(desc(abs(enrichment))) %>%
head()
# misc
pareg_post_processing(fit, dirname(snakemake@output$fname))
# save result
df %>%
write_csv(snakemake@output$fname)
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