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Filter non-finite data for plate analysis plots

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This commit is contained in:
Bryan Roessler
2024-09-25 16:54:58 -04:00
parent 1661f913d8
commit cbe363e8ad
1 changed files with 26 additions and 15 deletions
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41
qhtcp-workflow/apps/r/calculate_interaction_zscores.R
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@@ -634,6 +634,16 @@ generate_plate_analysis_plot_configs <- function(variables, stages = c("before",
for (var in variables) {
for (stage in stages) {
df_plot <- if (stage == "before") df_before else df_after
# Check for non-finite values in the y-variable
df_plot_filtered <- df_plot %>%
filter(is.finite(!!sym(var)))
# Count removed rows
removed_rows <- nrow(df_plot) - nrow(df_plot_filtered)
if (removed_rows > 0) {
message(sprintf("Removed %d non-finite values for variable %s during stage %s", removed_rows, var, stage))
}
# Adjust settings based on plot_type
if (plot_type == "scatter") {
@@ -660,7 +670,7 @@ generate_plate_analysis_plot_configs <- function(variables, stages = c("before",
return(plots)
}
generate_interaction_plot_configs <- function(df, variables, limits_map = NULL) {
generate_interaction_plot_configs <- function(df, limits_map = NULL) {
# Default limits_map if not provided
if (is.null(limits_map)) {
limits_map <- list(
@@ -682,8 +692,8 @@ generate_interaction_plot_configs <- function(df, variables, limits_map = NULL)
configs <- list()
for (variable in variables) {
y_range <- limits_map[[variable]]
for (var in names(limits_map)) {
y_range <- limits_map[[var]]
# Calculate annotation positions
y_min <- min(y_range)
@@ -699,8 +709,8 @@ generate_interaction_plot_configs <- function(df, variables, limits_map = NULL)
# Prepare linear model line
lm_line <- list(
intercept = df_filtered[[paste0("lm_intercept_", variable)]],
slope = df_filtered[[paste0("lm_slope_", variable)]]
intercept = df_filtered[[paste0("lm_intercept_", var)]],
slope = df_filtered[[paste0("lm_slope_", var)]]
)
# Calculate x-axis position for annotations
@@ -710,8 +720,8 @@ generate_interaction_plot_configs <- function(df, variables, limits_map = NULL)
# Generate annotations
annotations <- lapply(names(annotation_positions), function(annotation_name) {
label <- switch(annotation_name,
ZShift = paste("ZShift =", round(df_filtered[[paste0("Z_Shift_", variable)]], 2)),
lm_ZScore = paste("lm ZScore =", round(df_filtered[[paste0("Z_lm_", variable)]], 2)),
ZShift = paste("ZShift =", round(df_filtered[[paste0("Z_Shift_", var)]], 2)),
lm_ZScore = paste("lm ZScore =", round(df_filtered[[paste0("Z_lm_", var)]], 2)),
NG = paste("NG =", df_filtered$NG),
DB = paste("DB =", df_filtered$DB),
SM = paste("SM =", df_filtered$SM),
@@ -729,7 +739,7 @@ generate_interaction_plot_configs <- function(df, variables, limits_map = NULL)
plot_settings <- list(
df = df_filtered,
x_var = "conc_num_factor",
y_var = variable,
y_var = var,
ylim_vals = y_range,
annotations = annotations,
lm_line = lm_line,
@@ -1023,7 +1033,6 @@ main <- function() {
df = df,
variables = summary_vars,
group_vars = c("conc_num", "conc_num_factor"))$df_with_stats
message("Filtering non-finite data")
message("Calculating summary statistics after quality control")
ss <- calculate_summary_stats(
@@ -1033,6 +1042,8 @@ main <- function() {
df_na_ss <- ss$summary_stats
df_na_stats <- ss$df_with_stats
write.csv(df_na_ss, file = file.path(out_dir, "summary_stats_all_strains.csv"), row.names = FALSE)
# For plotting (ggplot warns on NAs)
df_na_stats_filtered <- df_na_stats %>% filter(across(all_of(summary_vars), is.finite))
df_na_stats <- df_na_stats %>%
mutate(
@@ -1153,20 +1164,20 @@ main <- function() {
plate_analysis_plot_configs <- generate_plate_analysis_plot_configs(
variables = summary_vars,
df_before = df_stats,
df_after = df_na_stats,
df_after = df_na_stats_filtered
)
plate_analysis_boxplot_configs <- generate_plate_analysis_plot_configs(
variables = summary_vars,
df_before = df_stats,
df_after = df_na_stats,
df_after = df_na_stats_filtered,
plot_type = "box"
)
plate_analysis_no_zeros_plot_configs <- generate_plate_analysis_plot_configs(
variables = summary_vars,
stages = c("after"), # Only after QC
df_after = df_no_zeros_stats,
df_after = df_no_zeros_stats
)
plate_analysis_no_zeros_boxplot_configs <- generate_plate_analysis_plot_configs(
@@ -1208,7 +1219,7 @@ main <- function() {
# TODO trying out some parallelization
# future::plan(future::multicore, workers = parallel::detectCores())
future::plan(future::multisession, workers = 3)
future::plan(future::multisession, workers = 3) # generate 3 plots in parallel
plot_configs <- list(
list(out_dir = out_dir_qc, filename = "L_vs_K_before_quality_control",
@@ -1318,11 +1329,11 @@ main <- function() {
# Create interaction plots
message("Generating reference interaction plots")
reference_plot_configs <- generate_interaction_plot_configs(zscore_interactions_reference_joined, interaction_vars)
reference_plot_configs <- generate_interaction_plot_configs(zscore_interactions_reference_joined)
generate_and_save_plots(out_dir, "interaction_plots_reference", reference_plot_configs, grid_layout = list(ncol = 4, nrow = 3))
message("Generating deletion interaction plots")
deletion_plot_configs <- generate_interaction_plot_configs(zscore_interactions_joined, interaction_vars)
deletion_plot_configs <- generate_interaction_plot_configs(zscore_interactions_joined)
generate_and_save_plots(out_dir, "interaction_plots", deletion_plot_configs, grid_layout = list(ncol = 4, nrow = 3))
# Define conditions for enhancers and suppressors