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Fix bg data references

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Bryan Roessler
2024-09-24 23:09:46 -04:00
parent 81174db065
commit 94c477ca28
1 changed files with 31 additions and 26 deletions
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57
qhtcp-workflow/apps/r/calculate_interaction_zscores.R
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@@ -207,23 +207,15 @@ calculate_interaction_scores <- function(df, max_conc, bg_stats, variables = c("
SM = sum(SM, na.rm = TRUE), SM = sum(SM, na.rm = TRUE),
num_non_removed_concs = total_conc_num - sum(DB, na.rm = TRUE) - 1, num_non_removed_concs = total_conc_num - sum(DB, na.rm = TRUE) - 1,
# Store the background data # Calculate raw data
WT_L = bg_stats$WT_L, Raw_Shift_L = first(mean_L) - bg_stats$L,
WT_K = bg_stats$WT_K, Raw_Shift_K = first(mean_K) - bg_stats$K,
WT_r = bg_stats$WT_r, Raw_Shift_r = first(mean_r) - bg_stats$r,
WT_AUC = bg_stats$WT_AUC, Raw_Shift_AUC = first(mean_AUC) - bg_stats$AUC,
WT_sd_L = bg_stats$WT_sd_L, Z_Shift_L = first(Raw_Shift_L) / bg_stats$sd_L,
WT_sd_K = bg_stats$WT_sd_K, Z_Shift_K = first(Raw_Shift_K) / bg_stats$sd_K,
WT_sd_r = bg_stats$WT_sd_r, Z_Shift_r = first(Raw_Shift_r) / bg_stats$sd_r,
WT_sd_AUC = bg_stats$WT_sd_AUC, Z_Shift_AUC = first(Raw_Shift_AUC) / bg_stats$sd_AUC,
Raw_Shift_L = first(mean_L) - bg_means$L,
Raw_Shift_K = first(mean_K) - bg_means$K,
Raw_Shift_r = first(mean_r) - bg_means$r,
Raw_Shift_AUC = first(mean_AUC) - bg_means$AUC,
Z_Shift_L = first(Raw_Shift_L) / bg_sd$L,
Z_Shift_K = first(Raw_Shift_K) / bg_sd$K,
Z_Shift_r = first(Raw_Shift_r) / bg_sd$r,
Z_Shift_AUC = first(Raw_Shift_AUC) / bg_sd$AUC,
Exp_L = WT_L + Raw_Shift_L, Exp_L = WT_L + Raw_Shift_L,
Exp_K = WT_K + Raw_Shift_K, Exp_K = WT_K + Raw_Shift_K,
Exp_r = WT_r + Raw_Shift_r, Exp_r = WT_r + Raw_Shift_r,
@@ -1070,18 +1062,31 @@ main <- function() {
write.csv(df_na_ss, file = file.path(out_dir, "summary_stats_all_strains.csv"), row.names = FALSE) write.csv(df_na_ss, file = file.path(out_dir, "summary_stats_all_strains.csv"), row.names = FALSE)
# df_na_filtered_stats <- process_data(df_na_stats, c("L"), filter_nf = TRUE) # df_na_filtered_stats <- process_data(df_na_stats, c("L"), filter_nf = TRUE)
# Pull the background means and standard deviations from zero concentration # Create background (WT) data columns
df_na_stats <- df_na_stats %>%
mutate(
WT_L = mean_L,
WT_K = mean_K,
WT_r = mean_r,
WT_AUC = mean_AUC,
WT_sd_L = sd_L,
WT_sd_K = sd_K,
WT_sd_r = sd_r,
WT_sd_AUC = sd_AUC
)
# Pull the background means and standard deviations from zero concentration for interactions
bg_stats <- df_na_stats %>% bg_stats <- df_na_stats %>%
filter(conc_num == 0) %>% filter(conc_num == 0) %>%
summarise( summarise(
WT_L = first(mean_L), L = first(mean_L),
WT_K = first(mean_K), K = first(mean_K),
WT_r = first(mean_r), r = first(mean_r),
WT_AUC = first(mean_AUC), AUC = first(mean_AUC),
WT_sd_L = first(sd_L), sd_L = first(sd_L),
WT_sd_K = first(sd_K), sd_K = first(sd_K),
WT_sd_r = first(sd_r), sd_r = first(sd_r),
WT_sd_AUC = first(sd_AUC) sd_AUC = first(sd_AUC)
) )
message("Calculating summary statistics after quality control excluding zero values") message("Calculating summary statistics after quality control excluding zero values")