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Fix accidental grouping by symbol

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Bryan Roessler
2024-10-07 06:44:36 -04:00
parent d978407b06
commit e187f96316
1 changed files with 13 additions and 6 deletions
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17
qhtcp-workflow/apps/r/calculate_interaction_zscores.R
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@@ -234,7 +234,7 @@ calculate_interaction_scores <- function(df, df_bg, type, overlap_threshold = 2)
# Join WT statistics to df
df <- df %>%
left_join(wt_stats, by = bg_group_vars)
left_join(wt_stats, by = c(bg_group_vars))
# Compute mean values at zero concentration
mean_zeroes <- df %>%
@@ -730,8 +730,7 @@ calculate_interaction_scores <- function(df, df_bg, type, overlap_threshold = 2)
"Raw_Shift_L", "Raw_Shift_K", "Raw_Shift_r", "Raw_Shift_AUC",
"R_Squared_L", "R_Squared_K", "R_Squared_r", "R_Squared_AUC",
# we need these for the interactions but the original code has the same names in both datasets
"Z_Shift_L", "Z_Shift_K", "Z_Shift_r", "Z_Shift_AUC",
"Z_lm_L", "Z_lm_K", "Z_lm_r", "Z_lm_AUC"
"Z_Shift_L", "Z_Shift_K", "Z_Shift_r", "Z_Shift_AUC"
)))
full_data <- calculations_no_overlap %>%
@@ -1435,6 +1434,12 @@ generate_correlation_plot_configs <- function(df, df_reference) {
x_var <- paste0("Z_lm_", rel$x) # predictor
y_var <- paste0("Z_lm_", rel$y) # response
# Skip this plot if there's no valid data
# if (all(is.na(df[[x_var]])) || all(is.na(df_reference[[x_var]])) ||
# all(is.na(df[[y_var]])) || all(is.na(df_reference[[y_var]]))) {
# next
# }
# Find the max and min of both dataframes for printing linear regression line
xmin <- min(c(min(df[[x_var]], na.rm = TRUE), min(df_reference[[x_var]], na.rm = TRUE)), na.rm = TRUE)
xmax <- max(c(max(df[[x_var]], na.rm = TRUE), max(df_reference[[x_var]], na.rm = TRUE)), na.rm = TRUE)
@@ -1802,9 +1807,10 @@ main <- function() {
message("Calculating reference strain interaction scores")
reference_results <- calculate_interaction_scores(df_reference_interaction_stats, df_bg_stats, "reference")
df_reference_calculations <- reference_results$calculations
df_reference_interactions_joined <- reference_results$full_data
df_reference_interactions <- reference_results$interactions
write.csv(reference_results$calculations, file = file.path(out_dir, "zscore_calculations_reference.csv"), row.names = FALSE)
write.csv(df_reference_calculations, file = file.path(out_dir, "zscore_calculations_reference.csv"), row.names = FALSE)
write.csv(df_reference_interactions, file = file.path(out_dir, "zscore_interactions_reference.csv"), row.names = FALSE)
# message("Generating reference interaction plots")
@@ -1832,9 +1838,10 @@ main <- function() {
message("Calculating deletion strain(s) interactions scores")
deletion_results <- calculate_interaction_scores(df_deletion_stats, df_bg_stats, "deletion")
df_calculations <- deletion_results$calculations
df_interactions <- deletion_results$interactions
df_interactions_joined <- deletion_results$full_data
write.csv(deletion_results$calculations, file = file.path(out_dir, "zscore_calculations.csv"), row.names = FALSE)
write.csv(df_calculations, file = file.path(out_dir, "zscore_calculations.csv"), row.names = FALSE)
write.csv(df_interactions, file = file.path(out_dir, "zscore_interactions.csv"), row.names = FALSE)
# message("Generating deletion interaction plots")