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

Refactor interaction plot configs

Browse Source
This commit is contained in:
Bryan Roessler
2024-09-16 14:19:52 -04:00
parent e07baf7a37
commit b13f2df26b
1 changed files with 62 additions and 69 deletions
Download Patch File Download Diff File Expand all files Collapse all files

131
qhtcp-workflow/apps/r/calculate_interaction_zscores.R
View File

@@ -578,102 +578,99 @@ generate_interaction_plot_configs <- function(df, variables) {
r = c(-0.65, 0.65),
AUC = c(-6500, 6500)
)
# Define functions to generate annotation labels
annotation_labels <- list(
ZShift = function(df, var) {
val <- df[[paste0("Z_Shift_", var)]]
paste("ZShift =", round(val, 2))
},
lm_ZScore = function(df, var) {
val <- df[[paste0("Z_lm_", var)]]
paste("lm ZScore =", round(val, 2))
},
NG = function(df, var) paste("NG =", df$NG),
DB = function(df, var) paste("DB =", df$DB),
SM = function(df, var) paste("SM =", df$SM)
)
results <- filter_data_for_plots(df, variables, limits_map)
df_filtered <- results$df_filtered
lm_lines <- filtered_results$lm_lines
# Iterate over each variable to create plot configurations
for (variable in variables) {
# Calculate x and y positions for annotations based on filtered data
x_levels <- levels(df_filtered$conc_num_factor)
num_levels <- length(x_levels)
x_pos <- (1 + num_levels) / 2 # Midpoint of x-axis positions
y_range <- limits_map[[variable]]
df_filtered <- filter_data_for_plots(df, variables, limits_map)$filtered_data
# Define annotation label functions
generate_annotation_labels <- function(df, var, annotation_name) {
switch(annotation_name,
ZShift = paste("ZShift =", round(df[[paste0("Z_Shift_", var)]], 2)),
lm_ZScore = paste("lm ZScore =", round(df[[paste0("Z_lm_", var)]], 2)),
NG = paste("NG =", df$NG),
DB = paste("DB =", df$DB),
SM = paste("SM =", df$SM),
NULL # Default case for unrecognized annotation names
)
}
# Define annotation positions relative to the y-axis range
calculate_annotation_positions <- function(y_range) {
y_min <- min(y_range)
y_max <- max(y_range)
y_span <- y_max - y_min
# Adjust y positions as fractions of y-span
annotation_positions <- list(
list(
ZShift = y_max - 0.1 * y_span,
lm_ZScore = y_max - 0.2 * y_span,
NG = y_min + 0.2 * y_span,
DB = y_min + 0.1 * y_span,
SM = y_min + 0.05 * y_span
)
}
# Create configurations for each variable
for (variable in variables) {
y_range <- limits_map[[variable]]
annotation_positions <- calculate_annotation_positions(y_range)
lm_line <- list(
intercept = df_filtered[[paste0("lm_intercept_", variable)]],
slope = df_filtered[[paste0("lm_slope_", variable)]]
)
# Determine x-axis midpoint
num_levels <- length(levels(df_filtered$conc_num_factor))
x_pos <- (1 + num_levels) / 2 # Midpoint of x-axis
# Generate annotations
annotations <- lapply(names(annotation_positions), function(annotation_name) {
label <- generate_annotation_labels(df_filtered, variable, annotation_name)
y_pos <- annotation_positions[[annotation_name]]
label_func <- annotation_labels[[annotation_name]]
if (!is.null(label_func)) {
label <- label_func(df_filtered, variable)
if (!is.null(label)) {
list(x = x_pos, y = y_pos, label = label)
} else {
message(paste("Warning: No annotation function found for", annotation_name))
message(paste("Warning: No annotation found for", annotation_name))
NULL
}
})
# Remove NULL annotations
annotations <- Filter(Negate(is.null), annotations)
# Create scatter plot config
configs[[length(configs) + 1]] <- list(
# Shared plot settings
plot_settings <- list(
df = df_filtered,
x_var = "conc_num_factor",
y_var = variable,
plot_type = "scatter",
title = sprintf("%s %s", df_filtered$OrfRep[1], df_filteredGene[1]),
ylim_vals = y_range,
annotations = annotations,
lm_line = lm_lines[[variable]],
error_bar = TRUE,
x_breaks = levels(df_filtered$conc_num_factor),
x_labels = levels(df_filtered$conc_num_factor),
x_label = unique(df$Drug[1]),
position = "jitter",
coord_cartesian = y_range # Use the actual y-limits
)
# Create box plot config
configs[[length(configs) + 1]] <- list(
df = df_filtered,
x_var = "conc_num_factor",
y_var = variable,
plot_type = "box",
title = sprintf("%s %s (Boxplot)", df_filtered$OrfRep[1], df_filtered$Gene[1]),
ylim_vals = y_range,
annotations = annotations,
error_bar = FALSE,
lm_line = lm_line,
x_breaks = levels(df_filtered$conc_num_factor),
x_labels = levels(df_filtered$conc_num_factor),
x_label = unique(df_filtered$Drug[1]),
coord_cartesian = y_range
coord_cartesian = y_range # Use the actual y-limits
)
# Scatter plot config
configs[[length(configs) + 1]] <- modifyList(plot_settings, list(
plot_type = "scatter",
title = sprintf("%s %s", df_filtered$OrfRep[1], df_filtered$Gene[1]),
error_bar = TRUE,
position = "jitter"
))
# Box plot config
configs[[length(configs) + 1]] <- modifyList(plot_settings, list(
plot_type = "box",
title = sprintf("%s %s (Boxplot)", df_filtered$OrfRep[1], df_filtered$Gene[1]),
error_bar = FALSE
))
}
return(configs)
}
generate_rank_plot_configs <- function(df, interaction_vars, rank_vars = c("L", "K"), is_lm = FALSE, adjust = FALSE) {
for (var in interaction_vars) {
@@ -789,7 +786,7 @@ filter_and_print_non_finite <- function(df, vars_to_check, print_vars) {
df %>% filter(if_all(all_of(vars_to_check), is.finite))
}
filter_data_for_plots <- function(df, variables, limits_map) {
filter_data_for_plots <- function(df, variables, limits_map = NULL) {
# Initialize lists to store lm lines and filtered data
lm_lines <- list()
@@ -830,11 +827,7 @@ filter_data_for_plots <- function(df, variables, limits_map) {
df_filtered <- df %>% filter(across(all_of(variables), ~ !is.na(.))) %>%
filter(across(all_of(variables), ~ between(., limits_map[[cur_column()]][1], limits_map[[cur_column()]][2]), .names = "filter_{col}"))
# Return the filtered dataframe and lm lines
return(list(
df_filtered = df_filtered,
lm_lines = lm_lines
))
return(df_filtered)
}
main <- function() {