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@@ -1232,9 +1232,9 @@ main <- function() {
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)
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# Generating quality control plots in parallel
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- # furrr::future_map(plot_configs, function(config) {
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- # generate_and_save_plots(config$out_dir, config$filename, config$plot_configs)
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- # }, .options = furrr_options(seed = TRUE))
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+ furrr::future_map(plot_configs, function(config) {
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+ generate_and_save_plots(config$out_dir, config$filename, config$plot_configs)
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+ }, .options = furrr_options(seed = TRUE))
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# Process background strains
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bg_strains <- c("YDL227C")
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@@ -1259,7 +1259,7 @@ main <- function() {
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ss_bg <- calculate_summary_stats(df_bg, summary_vars, group_vars = c("OrfRep", "conc_num", "conc_num_factor"))
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summary_stats_bg <- ss_bg$summary_stats
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write.csv(summary_stats_bg,
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- file = file.path(out_dir, paste0("SummaryStats_BackgroundStrains_", strain, ".csv")),
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+ file = file.path(out_dir, paste0("summary_stats_background_strain_", strain, ".csv")),
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row.names = FALSE)
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# Set the missing values to the highest theoretical value at each drug conc for L
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@@ -1449,7 +1449,7 @@ main <- function() {
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correlation_plot_configs <- generate_correlation_plot_configs(zscores_interactions_filtered)
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generate_and_save_plots(
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out_dir = out_dir,
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- filename = "Avg_Zscore_vs_lm_NA_rm",
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+ filename = "Correlation_CPPs",
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plot_configs = correlation_plot_configs,
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grid_layout = list(ncol = 2, nrow = 2))
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})
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