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Separate adjustments from ranks

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This commit is contained in:
Bryan Roessler
2024-09-16 12:21:40 -04:00
parent 1dfb5d5084
commit 22236fef49
1 changed files with 19 additions and 25 deletions
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44
qhtcp-workflow/apps/r/calculate_interaction_zscores.R
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@@ -709,23 +709,21 @@ generate_interaction_plot_configs <- function(df, variables) {
generate_rank_plot_configs <- function(df, interaction_vars, rank_vars = c("L", "K"), is_lm = FALSE, adjust = FALSE) {
# Adjust missing values and compute ranks for each interaction variable
if (adjust) {
for (var in interaction_vars) {
avg_zscore_col <- paste0("Avg_Zscore_", var)
z_lm_col <- paste0("Z_lm_", var)
rank_col <- paste0("Rank_", var)
rank_lm_col <- paste0("Rank_lm_", var)
for (var in interaction_vars) {
avg_zscore_col <- paste0("Avg_Zscore_", var)
z_lm_col <- paste0("Z_lm_", var)
rank_col <- paste0("Rank_", var)
rank_lm_col <- paste0("Rank_lm_", var)
if (adjust) {
# Replace NA with 0.001 for interaction variables
df[[avg_zscore_col]] <- if_else(is.na(df[[avg_zscore_col]]), 0.001, df[[avg_zscore_col]])
df[[z_lm_col]] <- if_else(is.na(df[[z_lm_col]]), 0.001, df[[z_lm_col]])
# Compute ranks for interaction variables
df[[rank_col]] <- rank(df[[avg_zscore_col]], na.last = "keep")
df[[rank_lm_col]] <- rank(df[[z_lm_col]], na.last = "keep")
}
# Compute ranks for interaction variables
df[[rank_col]] <- rank(df[[avg_zscore_col]], na.last = "keep")
df[[rank_lm_col]] <- rank(df[[z_lm_col]], na.last = "keep")
}
# Initialize list to store plot configurations
@@ -782,11 +780,8 @@ generate_rank_plot_configs <- function(df, interaction_vars, rank_vars = c("L",
)
}
}
return(list(
adjusted_df = df,
plot_configs = configs
))
return(configs)
}
generate_correlation_plot_configs <- function(df, variables) {
@@ -1230,7 +1225,7 @@ main <- function() {
interaction_vars = interaction_vars,
is_lm = FALSE,
adjust = TRUE
)$plot_configs
)
# Save the generated rank plots for L and K
generate_and_save_plots(output_dir = out_dir, file_name = "RankPlots",
@@ -1242,27 +1237,26 @@ main <- function() {
interaction_vars = interaction_vars,
is_lm = TRUE,
adjust = TRUE
)$plot_configs
)
# Save the linear model based rank plots for L and K
generate_and_save_plots(output_dir = out_dir, file_name = "RankPlots_lm",
plot_configs = rank_lm_plot_configs, grid_layout = list(ncol = 3, nrow = 2))
message("Filtering and regenerating rank plots")
# Filter rows where either Z_lm_L or Avg_Zscore_L is not NA
# Formerly X_NArm
zscores_interactions_filtered <- zscores_interactions %>%
group_by(across(all_of(orf_group_vars))) %>%
filter(!is.na(Z_lm_L) | !is.na(Avg_Zscore_L)) %>%
ungroup()
# Final filtered correlation calculations and Overlap column
zscores_interactions_filtered <- zscores_interactions_filtered %>%
ungroup() %>%
rowwise() %>%
mutate(
lm_R_squared_L = if (n() > 1) summary(lm(Z_lm_L ~ Avg_Zscore_L))$r.squared else NA,
lm_R_squared_K = if (n() > 1) summary(lm(Z_lm_K ~ Avg_Zscore_K))$r.squared else NA,
lm_R_squared_r = if (n() > 1) summary(lm(Z_lm_r ~ Avg_Zscore_r))$r.squared else NA,
lm_R_squared_AUC = if (n() > 1) summary(lm(Z_lm_AUC ~ Avg_Zscore_AUC))$r.squared else NA,
Overlap = case_when(
Z_lm_L >= 2 & Avg_Zscore_L >= 2 ~ "Deletion Enhancer Both",
Z_lm_L <= -2 & Avg_Zscore_L <= -2 ~ "Deletion Suppressor Both",