bryan/hartman-server
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Improve WT groupings

Browse Source
This commit is contained in:
Bryan Roessler
2024-10-05 06:00:25 -04:00
parent e6f5aab81f
commit f207e40efd
1 changed files with 15 additions and 34 deletions
Download Patch File Download Diff File Expand all files Collapse all files

49
qhtcp-workflow/apps/r/calculate_interaction_zscores.R
View File

@@ -210,7 +210,7 @@ calculate_interaction_scores <- function(df, df_bg, group_vars, overlap_threshol
# Calculate WT statistics from df_bg
wt_stats <- df_bg %>%
filter(conc_num == 0) %>%
group_by(across(all_of(group_vars)), conc_num, conc_num_factor_factor) %>%
summarise(
WT_L = mean(mean_L, na.rm = TRUE),
WT_sd_L = mean(sd_L, na.rm = TRUE),
@@ -219,21 +219,13 @@ calculate_interaction_scores <- function(df, df_bg, group_vars, overlap_threshol
WT_r = mean(mean_r, na.rm = TRUE),
WT_sd_r = mean(sd_r, na.rm = TRUE),
WT_AUC = mean(mean_AUC, na.rm = TRUE),
WT_sd_AUC = mean(sd_AUC, na.rm = TRUE)
WT_sd_AUC = mean(sd_AUC, na.rm = TRUE),
.groups = "drop"
)
# Add WT statistics to df
# Join WT stats back to df
df <- df %>%
mutate(
WT_L = wt_stats$WT_L,
WT_sd_L = wt_stats$WT_sd_L,
WT_K = wt_stats$WT_K,
WT_sd_K = wt_stats$WT_sd_K,
WT_r = wt_stats$WT_r,
WT_sd_r = wt_stats$WT_sd_r,
WT_AUC = wt_stats$WT_AUC,
WT_sd_AUC = wt_stats$WT_sd_AUC
)
left_join(wt_stats, by = c(group_vars, "conc_num", "conc_num_factor_factor"))
# Compute mean values at zero concentration
mean_L_zero_df <- df %>%
@@ -804,16 +796,6 @@ generate_scatter_plot <- function(plot, config) {
color = smooth_color
)
}
# For now I want to try and hardcode it
# else {
# plot <- plot +
# geom_smooth(
# method = "lm",
# se = FALSE,
# color = smooth_color
# )
# }
}
# Add SD Bands if specified
@@ -1077,8 +1059,8 @@ generate_interaction_plot_configs <- function(df_summary, df_interaction, type)
title_size = rel(1.3),
coord_cartesian = y_limits,
annotations = list(
list(x = 1, y = y_limits[2] - 0.1 * y_span, label = paste(" ZShift =", round(Z_Shift_value, 2))),
list(x = 1, y = y_limits[2] - 0.2 * y_span, label = paste(" lm ZScore =", round(Z_lm_value, 2))),
list(x = 1, y = y_limits[2] - 0.1 * y_span, label = paste(" ZShift =", round(Z_Shift_value, 2))),
list(x = 1, y = y_limits[2] - 0.2 * y_span, label = paste(" lm ZScore =", round(Z_lm_value, 2))),
# list(x = 1, y = y_limits[2] - 0.3 * y_span, label = paste(" R-squared =", round(R_squared_value, 2))),
list(x = 1, y = y_limits[1] + 0.1 * y_span, label = paste("NG =", NG_value)),
list(x = 1, y = y_limits[1] + 0.05 * y_span, label = paste("DB =", DB_value)),
@@ -1582,11 +1564,10 @@ main <- function() {
)$df_with_stats
message("Calculating reference strain interaction scores")
results <- calculate_interaction_scores(df_reference_interaction_stats,
df_bg_stats, group_vars = c("OrfRep", "Gene", "num", "Drug"))
df_reference_calculations <- results$calculations
df_reference_interactions <- results$interactions
df_reference_interactions_joined <- results$full_data
reference_results <- calculate_interaction_scores(df_reference_interaction_stats, df_bg_stats, group_vars = c("OrfRep", "Gene", "num", "Drug"))
df_reference_calculations <- reference_results$calculations
df_reference_interactions <- reference_results$interactions
df_reference_interactions_joined <- reference_results$full_data
write.csv(df_reference_calculations, file = file.path(out_dir, "zscore_calculations_reference.csv"), row.names = FALSE)
write.csv(df_reference_interactions, file = file.path(out_dir, "zscore_interactions_reference.csv"), row.names = FALSE)
@@ -1614,10 +1595,10 @@ main <- function() {
)$df_with_stats
message("Calculating deletion strain(s) interactions scores")
results <- calculate_interaction_scores(df_deletion_stats, df_bg_stats, group_vars = c("OrfRep", "Gene", "Drug"))
df_calculations <- results$calculations
df_interactions <- results$interactions
df_interactions_joined <- results$full_data
deletion_results <- calculate_interaction_scores(df_deletion_stats, df_bg_stats, group_vars = c("OrfRep", "Gene", "Drug"))
df_calculations <- deletion_results$calculations
df_interactions <- deletion_results$interactions
df_interactions_joined <- deletion_results$full_data
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)