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Add correlation plots

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This commit is contained in:
Bryan Roessler
2024-09-10 17:50:15 -04:00
parent 9ae08be8b5
commit 5518005d03
1 changed files with 114 additions and 78 deletions
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192
qhtcp-workflow/apps/r/calculate_interaction_zscores.R
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@@ -530,60 +530,6 @@ generate_interaction_plot_configs <- function(df, variables) {
return(plot_configs)
}
generate_rank_plot_configs <- function(df, rank_var, zscore_var, label_prefix, is_lm = FALSE) {
configs <- list()
# Adjust titles for _lm plots if is_lm is TRUE
plot_title_prefix <- if (is_lm) "Interaction Z score vs. Rank for" else "Average Z score vs. Rank for"
for (sd_band in c(1, 2, 3)) {
# Annotated version (with text)
configs[[length(configs) + 1]] <- list(
df = df,
x_var = rank_var,
y_var = zscore_var,
plot_type = "rank",
title = paste(plot_title_prefix, label_prefix, "above", sd_band, "SD"),
sd_band = sd_band,
enhancer_label = list(
x = nrow(df) / 2, y = 10,
label = paste("Deletion Enhancers =", nrow(df[df[[zscore_var]] >= sd_band, ]))
),
suppressor_label = list(
x = nrow(df) / 2, y = -10,
label = paste("Deletion Suppressors =", nrow(df[df[[zscore_var]] <= -sd_band, ]))
)
)
# Non-annotated version (_notext)
configs[[length(configs) + 1]] <- list(
df = df,
x_var = rank_var,
y_var = zscore_var,
plot_type = "rank",
title = paste(plot_title_prefix, label_prefix, "above", sd_band, "SD"),
sd_band = sd_band,
enhancer_label = NULL, # No annotations for _notext
suppressor_label = NULL # No annotations for _notext
)
}
return(configs)
}
generate_correlation_plot_configs <- function(df, lm_list, lm_summaries) {
lapply(seq_along(lm_list), function(i) {
r_squared <- round(lm_summaries[[i]]$r.squared, 3)
list(
x_var = names(lm_list)[i][1],
y_var = names(lm_list)[i][2],
plot_type = "scatter",
title = paste("Correlation between", names(lm_list)[i][1], "and", names(lm_list)[i][2]),
annotations = list(list(x = 0, y = 0, label = paste("R-squared =", r_squared)))
)
})
}
# Adjust missing values and calculate ranks
adjust_missing_and_rank <- function(df, variables) {
@@ -599,6 +545,71 @@ adjust_missing_and_rank <- function(df, variables) {
return(df)
}
generate_rank_plot_configs <- function(df, rank_var, zscore_var, var, is_lm = FALSE) {
configs <- list()
# Adjust titles for _lm plots if is_lm is TRUE
plot_title_prefix <- if (is_lm) "Interaction Z score vs. Rank for" else "Average Z score vs. Rank for"
# Annotated version (with text)
for (sd_band in c(1, 2, 3)) {
configs[[length(configs) + 1]] <- list(
df = df,
x_var = rank_var,
y_var = zscore_var,
plot_type = "rank",
title = paste(plot_title_prefix, var, "above", sd_band, "SD"),
sd_band = sd_band,
enhancer_label = list(
x = nrow(df) / 2, y = 10,
label = paste("Deletion Enhancers =", nrow(df[df[[zscore_var]] >= sd_band, ]))
),
suppressor_label = list(
x = nrow(df) / 2, y = -10,
label = paste("Deletion Suppressors =", nrow(df[df[[zscore_var]] <= -sd_band, ]))
)
)
}
# Non-annotated version (_notext)
for (sd_band in c(1, 2, 3)) {
configs[[length(configs) + 1]] <- list(
df = df,
x_var = rank_var,
y_var = zscore_var,
plot_type = "rank",
title = paste(plot_title_prefix, var, "above", sd_band, "SD"),
sd_band = sd_band,
enhancer_label = NULL, # No annotations for _notext
suppressor_label = NULL # No annotations for _notext
)
}
return(configs)
}
generate_correlation_plot_configs <- function(df, variables) {
plot_configs <- list()
for (variable in variables) {
z_lm_var <- paste0("Z_lm_", variable)
avg_zscore_var <- paste0("Avg_Zscore_", variable)
lm_r_squared_col <- paste0("lm_R_squared_", variable)
plot_configs[[length(plot_configs) + 1]] <- list(
df = df,
x_var = avg_zscore_var,
y_var = z_lm_var,
plot_type = "correlation",
title = paste("Avg Zscore vs lm", variable),
color_var = "Overlap",
correlation_text = paste("R-squared =", round(df[[lm_r_squared_col]][1], 2))
)
}
return(plot_configs)
}
main <- function() {
lapply(names(args$experiments), function(exp_name) {
exp <- args$experiments[[exp_name]]
@@ -674,10 +685,8 @@ main <- function() {
write.csv(l_within_2sd_k_stats, file = file.path(out_dir_qc, "Max_Observed_L_Vals_for_spots_within_2sd_k.csv"), row.names = FALSE)
write.csv(l_outside_2sd_k_stats, file = file.path(out_dir, "Max_Observed_L_Vals_for_spots_outside_2sd_k.csv"), row.names = FALSE)
# Plots
# Print quality control graphs before removing data due to contamination and
# adjusting missing data to max theoretical values
# Plot configurations
# Each plots list corresponds to a file
message("Generating QC plot configurations")
l_vs_k_plots <- list(
list(df = df, x_var = "L", y_var = "K", plot_type = "scatter",
@@ -820,9 +829,9 @@ main <- function() {
# Recalculate summary statistics for the background strain
message("Calculating summary statistics for background strain")
ss <- calculate_summary_stats(df_bg, variables, group_vars = c("OrfRep", "conc_num", "conc_num_factor"))
summary_stats_bg <- ss$summary_stats
df_bg_stats <- ss$df_with_stats
ss_bg <- calculate_summary_stats(df_bg, variables, group_vars = c("OrfRep", "conc_num", "conc_num_factor"))
summary_stats_bg <- ss_bg$summary_stats
# df_bg_stats <- ss_bg$df_with_stats
write.csv(summary_stats_bg,
file = file.path(out_dir, paste0("SummaryStats_BackgroundStrains_", strain, ".csv")),
row.names = FALSE)
@@ -935,6 +944,7 @@ main <- function() {
write.csv(suppressors_lm_K,
file = file.path(out_dir, "ZScores_Interaction_Deletion_Suppressors_K_lm.csv"), row.names = FALSE)
# TODO needs explanation
zscores_interactions_adjusted <- adjust_missing_and_rank(zscores_interactions)
rank_plot_configs <- c(
@@ -945,30 +955,56 @@ main <- function() {
plot_configs = rank_plot_config, grid_layout = list(ncol = 3, nrow = 2))
rank_lm_plot_config <- c(
generate_rank_lm_plot_configs(zscores_interactions_adjusted, "Rank_lm_L", "Z_lm_L", "L"),
generate_rank_lm_plot_configs(zscores_interactions_adjusted, "Rank_lm_K", "Z_lm_K", "K")
generate_rank_plot_configs(zscores_interactions_adjusted, "Rank_lm_L", "Z_lm_L", "L", is_lm = TRUE),
generate_rank_plot_configs(zscores_interactions_adjusted, "Rank_lm_K", "Z_lm_K", "K", is_lm = TRUE)
)
generate_and_save_plots(output_dir = out_dir, file_name = "RankPlots_lm",
plot_configs = rank_lm_plot_config, grid_layout = list(ncol = 3, nrow = 2))
# interaction_scores_filtered
# Formerly X_NArm
zscores_interactions_filtered <- zscores_interactions %>%
group_by(across(all_of(group_vars))) %>%
filter(!is.na(Z_lm_L) | !is.na(Avg_Zscore_L))
zscores_interactions_filtered <- zscores_interactions_filtered %>%
mutate(
Overlap = case_when(
Z_lm_L >= 2 & Avg_Zscore_L >= 2 ~ "Deletion Enhancer Both",
Z_lm_L <= -2 & Avg_Zscore_L <= -2 ~ "Deletion Suppressor Both",
Z_lm_L >= 2 & Avg_Zscore_L <= 2 ~ "Deletion Enhancer lm only",
Z_lm_L <= -2 & Avg_Zscore_L >= -2 ~ "Deletion Suppressor lm only",
Z_lm_L >= 2 & Avg_Zscore_L <= -2 ~ "Deletion Enhancer lm, Deletion Suppressor Avg Z score",
Z_lm_L <= -2 & Avg_Zscore_L >= 2 ~ "Deletion Suppressor lm, Deletion Enhancer Avg Z score",
TRUE ~ "No Effect"
),
lm_R_squared_L = summary(lm(Z_lm_L ~ Avg_Zscore_L))$r.squared,
lm_R_squared_K = summary(lm(Z_lm_K ~ Avg_Zscore_K))$r.squared,
lm_R_squared_r = summary(lm(Z_lm_r ~ Avg_Zscore_r))$r.squared,
lm_R_squared_AUC = summary(lm(Z_lm_AUC ~ Avg_Zscore_AUC))$r.squared
) %>%
ungroup()
rank_plot_configs <- c(
generate_rank_plot_configs(zscores_interactions_filtered, "Rank_L", "Avg_Zscore_L", "L"),
generate_rank_plot_configs(zscores_interactions_filtered, "Rank_K", "Avg_Zscore_K", "K")
)
generate_and_save_plots(output_dir = out_dir, file_name = "RankPlots",
plot_configs = rank_plot_configs, grid_layout = list(ncol = 3, nrow = 2))
rank_lm_plot_configs <- c(
generate_rank_plot_configs(zscores_interactions_filtered, "Rank_lm_L", "Z_lm_L", "L", is_lm = TRUE),
generate_rank_plot_configs(zscores_interactions_filtered, "Rank_lm_K", "Z_lm_K", "K", is_lm = TRUE)
)
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))
correlation_plot_configs <- generate_correlation_plot_configs(zscores_interactions_filtered, variables)
generate_and_save_plots(output_dir = out_dir, file_name = "Avg_Zscore_vs_lm_NA_rm",
plot_configs = correlation_plot_configs, grid_layout = list(ncol = 2, nrow = 2))
# lm_summaries <- lapply(lm_list, summary)
# correlation_plot_configs <- generate_correlation_plot_configs(zscores_interactions_filtered, lm_list, lm_summaries)
# generate_and_save_plots(zscores_interactions_filtered, output_dir, correlation_plot_configs)
})
})
}
main()
# # Correlation plots
# lm_list <- list(
# lm(Z_lm_K ~ Z_lm_L, data = zscores_interactions_filtered),
# lm(Z_lm_r ~ Z_lm_L, data = zscores_interactions_filtered),
# lm(Z_lm_AUC ~ Z_lm_L, data = zscores_interactions_filtered),
# lm(Z_lm_r ~ Z_lm_K, data = zscores_interactions_filtered),
# lm(Z_lm_AUC ~ Z_lm_K, data = zscores_interactions_filtered),
# lm(Z_lm_AUC ~ Z_lm_r, data = zscores_interactions_filtered)
# )