Revert map2(), what a disaster
This commit is contained in:
@@ -217,6 +217,20 @@ calculate_interaction_scores <- function(df, df_bg, type, overlap_threshold = 2)
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group_vars <- c("OrfRep", "Gene", "Drug")
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group_vars <- c("OrfRep", "Gene", "Drug")
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}
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}
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perform_lm_simple <- function(x, y, max_conc) {
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if (all(is.na(x)) || all(is.na(y)) || length(x[!is.na(x)]) == 0 || length(y[!is.na(y)]) == 0) {
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return(list(intercept = NA, slope = NA, r_squared = NA, score = NA))
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} else {
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fit <- lm(y ~ x)
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return(list(
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intercept = coef(fit)[1],
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slope = coef(fit)[2],
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r_squared = summary(fit)$r.squared,
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score = max_conc * coef(fit)[2] + coef(fit)[1]
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))
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}
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}
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# Calculate WT statistics from df_bg
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# Calculate WT statistics from df_bg
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wt_stats <- df_bg %>%
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wt_stats <- df_bg %>%
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group_by(across(all_of(bg_group_vars))) %>%
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group_by(across(all_of(bg_group_vars))) %>%
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@@ -301,78 +315,35 @@ calculate_interaction_scores <- function(df, df_bg, type, overlap_threshold = 2)
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calculations <- calculations %>%
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calculations <- calculations %>%
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group_by(across(all_of(group_vars))) %>%
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group_by(across(all_of(group_vars))) %>%
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mutate(
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mutate(
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lm_L = map2(.x = Delta_L, .y = conc_num_factor, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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# Apply the simple LM function for each variable
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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lm_L = list(perform_lm_simple(Delta_L, conc_num_factor, max_conc)),
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} else {
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lm_K = list(perform_lm_simple(Delta_K, conc_num_factor, max_conc)),
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lm(.x ~ .y) %>% {
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lm_r = list(perform_lm_simple(Delta_r, conc_num_factor, max_conc)),
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list(
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lm_AUC = list(perform_lm_simple(Delta_AUC, conc_num_factor, max_conc)),
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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lm_K = map2(.x = Delta_K, .y = conc_num_factor, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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} else {
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lm(.x ~ .y) %>% {
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list(
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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lm_r = map2(.x = Delta_r, .y = conc_num_factor, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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} else {
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lm(.x ~ .y) %>% {
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list(
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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lm_AUC = map2(.x = Delta_AUC, .y = conc_num_factor, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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} else {
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lm(.x ~ .y) %>% {
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list(
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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# Extract coefficients and statistics for each model
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# Extract coefficients and statistics for each model
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lm_intercept_L = map_dbl(lm_L, "intercept"),
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lm_intercept_L = lm_L[[1]]$intercept,
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lm_slope_L = map_dbl(lm_L, "slope"),
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lm_slope_L = lm_L[[1]]$slope,
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R_Squared_L = map_dbl(lm_L, "r_squared"),
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R_Squared_L = lm_L[[1]]$r_squared,
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lm_Score_L = map_dbl(lm_L, "score"),
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lm_Score_L = lm_L[[1]]$score,
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lm_intercept_K = map_dbl(lm_K, "intercept"),
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lm_intercept_K = lm_K[[1]]$intercept,
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lm_slope_K = map_dbl(lm_K, "slope"),
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lm_slope_K = lm_K[[1]]$slope,
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R_Squared_K = map_dbl(lm_K, "r_squared"),
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R_Squared_K = lm_K[[1]]$r_squared,
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lm_Score_K = map_dbl(lm_K, "score"),
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lm_Score_K = lm_K[[1]]$score,
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lm_intercept_r = map_dbl(lm_r, "intercept"),
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lm_intercept_r = lm_r[[1]]$intercept,
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lm_slope_r = map_dbl(lm_r, "slope"),
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lm_slope_r = lm_r[[1]]$slope,
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R_Squared_r = map_dbl(lm_r, "r_squared"),
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R_Squared_r = lm_r[[1]]$r_squared,
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lm_Score_r = map_dbl(lm_r, "score"),
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lm_Score_r = lm_r[[1]]$score,
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lm_intercept_AUC = map_dbl(lm_AUC, "intercept"),
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lm_intercept_AUC = lm_AUC[[1]]$intercept,
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lm_slope_AUC = map_dbl(lm_AUC, "slope"),
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lm_slope_AUC = lm_AUC[[1]]$slope,
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R_Squared_AUC = map_dbl(lm_AUC, "r_squared"),
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R_Squared_AUC = lm_AUC[[1]]$r_squared,
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lm_Score_AUC = map_dbl(lm_AUC, "score")
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lm_Score_AUC = lm_AUC[[1]]$score
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) %>%
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) %>%
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select(-lm_L, -lm_K, -lm_r, -lm_AUC) %>%
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select(-lm_L, -lm_K, -lm_r, -lm_AUC) %>%
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ungroup()
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ungroup()
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# For interaction plot error bars
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# For interaction plot error bars
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delta_means_sds <- calculations %>%
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delta_means_sds <- calculations %>%
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@@ -509,179 +480,70 @@ calculate_interaction_scores <- function(df, df_bg, type, overlap_threshold = 2)
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Z_lm_L <= -overlap_threshold & Avg_Zscore_L >= overlap_threshold ~ "Deletion Suppressor lm, Deletion Enhancer Avg Zscore",
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Z_lm_L <= -overlap_threshold & Avg_Zscore_L >= overlap_threshold ~ "Deletion Suppressor lm, Deletion Enhancer Avg Zscore",
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TRUE ~ "No Effect"
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TRUE ~ "No Effect"
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),
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),
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lm_L = map2(.x = Z_lm_L, .y = Avg_Zscore_L, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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# Apply the perform_lm_simple function for each variable pair
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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lm_L = list(perform_lm_simple(Z_lm_L, Avg_Zscore_L, max_conc)),
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} else {
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lm_K = list(perform_lm_simple(Z_lm_K, Avg_Zscore_K, max_conc)),
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lm(.y ~ .x) %>% {
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lm_r = list(perform_lm_simple(Z_lm_r, Avg_Zscore_r, max_conc)),
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list(
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lm_AUC = list(perform_lm_simple(Z_lm_AUC, Avg_Zscore_AUC, max_conc)),
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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lm_K = map2(.x = Z_lm_K, .y = Avg_Zscore_K, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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} else {
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lm(.y ~ .x) %>% {
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list(
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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lm_r = map2(.x = Z_lm_r, .y = Avg_Zscore_r, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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} else {
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lm(.y ~ .x) %>% {
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list(
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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lm_AUC = map2(.x = Z_lm_AUC, .y = Avg_Zscore_AUC, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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} else {
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lm(.y ~ .x) %>% {
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list(
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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# For correlation plots
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# Correlation models for various pairs
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Z_lm_K_L = map2(.x = Z_lm_K, .y = Z_lm_L, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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Z_lm_K_L = list(perform_lm_simple(Z_lm_K, Z_lm_L, max_conc)),
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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Z_lm_r_L = list(perform_lm_simple(Z_lm_r, Z_lm_L, max_conc)),
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} else {
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Z_lm_R_AUC_L = list(perform_lm_simple(Z_lm_AUC, Z_lm_L, max_conc)),
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lm(.y ~ .x) %>% {
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Z_lm_R_r_K = list(perform_lm_simple(Z_lm_r, Z_lm_K, max_conc)),
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list(
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Z_lm_R_AUC_K = list(perform_lm_simple(Z_lm_AUC, Z_lm_K, max_conc)),
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intercept = coef(.)[1],
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Z_lm_R_AUC_r = list(perform_lm_simple(Z_lm_AUC, Z_lm_r, max_conc)),
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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Z_lm_r_L = map2(.x = Z_lm_r, .y = Z_lm_L, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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} else {
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lm(.y ~ .x) %>% {
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list(
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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Z_lm_R_AUC_L = map2(.x = Z_lm_AUC, .y = Z_lm_L, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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} else {
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lm(.y ~ .x) %>% {
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list(
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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Z_lm_R_r_K = map2(.x = Z_lm_r, .y = Z_lm_K, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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} else {
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lm(.y ~ .x) %>% {
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list(
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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Z_lm_R_AUC_K = map2(.x = Z_lm_AUC, .y = Z_lm_K, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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} else {
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lm(.y ~ .x) %>% {
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list(
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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Z_lm_R_AUC_r = map2(.x = Z_lm_AUC, .y = Z_lm_r, ~ if (all(is.na(.x)) || all(is.na(.y)) || length(.x[!is.na(.x)]) == 0) {
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list(intercept = NA, slope = NA, r_squared = NA, score = NA)
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} else {
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lm(.y ~ .x) %>% {
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list(
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intercept = coef(.)[1],
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slope = coef(.)[2],
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r_squared = summary(.)$r.squared,
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score = max_conc * coef(.)[2] + coef(.)[1]
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)
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}
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}),
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# Extract coefficients and statistics for each model
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# Extract coefficients and statistics for each model
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lm_rank_intercept_L = map_dbl(lm_L, "intercept"),
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lm_rank_intercept_L = lm_L[[1]]$intercept,
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lm_rank_slope_L = map_dbl(lm_L, "slope"),
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lm_rank_slope_L = lm_L[[1]]$slope,
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R_Squared_L = map_dbl(lm_L, "r_squared"),
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R_Squared_L = lm_L[[1]]$r_squared,
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lm_Score_L = map_dbl(lm_L, "score"),
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lm_Score_L = lm_L[[1]]$score,
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lm_intercept_K = map_dbl(lm_K, "intercept"),
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lm_intercept_K = lm_K[[1]]$intercept,
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lm_slope_K = map_dbl(lm_K, "slope"),
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lm_slope_K = lm_K[[1]]$slope,
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R_Squared_K = map_dbl(lm_K, "r_squared"),
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R_Squared_K = lm_K[[1]]$r_squared,
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lm_Score_K = map_dbl(lm_K, "score"),
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lm_Score_K = lm_K[[1]]$score,
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lm_intercept_r = map_dbl(lm_r, "intercept"),
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lm_intercept_r = lm_r[[1]]$intercept,
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lm_slope_r = map_dbl(lm_r, "slope"),
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lm_slope_r = lm_r[[1]]$slope,
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R_Squared_r = map_dbl(lm_r, "r_squared"),
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R_Squared_r = lm_r[[1]]$r_squared,
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lm_Score_r = map_dbl(lm_r, "score"),
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lm_Score_r = lm_r[[1]]$score,
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lm_intercept_AUC = map_dbl(lm_AUC, "intercept"),
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lm_intercept_AUC = lm_AUC[[1]]$intercept,
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lm_slope_AUC = map_dbl(lm_AUC, "slope"),
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lm_slope_AUC = lm_AUC[[1]]$slope,
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R_Squared_AUC = map_dbl(lm_AUC, "r_squared"),
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R_Squared_AUC = lm_AUC[[1]]$r_squared,
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lm_Score_AUC = map_dbl(lm_AUC, "score"),
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lm_Score_AUC = lm_AUC[[1]]$score,
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Z_lm_intercept_K_L = map_dbl(Z_lm_K_L, "intercept"),
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Z_lm_intercept_K_L = Z_lm_K_L[[1]]$intercept,
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Z_lm_slope_K_L = map_dbl(Z_lm_K_L, "slope"),
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Z_lm_slope_K_L = Z_lm_K_L[[1]]$slope,
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Z_lm_R_squared_K_L = map_dbl(Z_lm_K_L, "r_squared"),
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Z_lm_R_squared_K_L = Z_lm_K_L[[1]]$r_squared,
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Z_lm_Score_K_L = map_dbl(Z_lm_K_L, "score"),
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Z_lm_Score_K_L = Z_lm_K_L[[1]]$score,
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Z_lm_intercept_r_L = map_dbl(Z_lm_r_L, "intercept"),
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Z_lm_intercept_r_L = Z_lm_r_L[[1]]$intercept,
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Z_lm_slope_r_L = map_dbl(Z_lm_r_L, "slope"),
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Z_lm_slope_r_L = Z_lm_r_L[[1]]$slope,
|
||||||
Z_lm_R_squared_r_L = map_dbl(Z_lm_r_L, "r_squared"),
|
Z_lm_R_squared_r_L = Z_lm_r_L[[1]]$r_squared,
|
||||||
Z_lm_Score_r_L = map_dbl(Z_lm_r_L, "score"),
|
Z_lm_Score_r_L = Z_lm_r_L[[1]]$score,
|
||||||
|
|
||||||
Z_lm_intercept_R_AUC_L = map_dbl(Z_lm_R_AUC_L, "intercept"),
|
Z_lm_intercept_R_AUC_L = Z_lm_R_AUC_L[[1]]$intercept,
|
||||||
Z_lm_slope_R_AUC_L = map_dbl(Z_lm_R_AUC_L, "slope"),
|
Z_lm_slope_R_AUC_L = Z_lm_R_AUC_L[[1]]$slope,
|
||||||
Z_lm_R_squared_R_AUC_L = map_dbl(Z_lm_R_AUC_L, "r_squared"),
|
Z_lm_R_squared_R_AUC_L = Z_lm_R_AUC_L[[1]]$r_squared,
|
||||||
Z_lm_Score_R_AUC_L = map_dbl(Z_lm_R_AUC_L, "score"),
|
Z_lm_Score_R_AUC_L = Z_lm_R_AUC_L[[1]]$score,
|
||||||
|
|
||||||
Z_lm_intercept_R_r_K = map_dbl(Z_lm_R_r_K, "intercept"),
|
Z_lm_intercept_R_r_K = Z_lm_R_r_K[[1]]$intercept,
|
||||||
Z_lm_slope_R_r_K = map_dbl(Z_lm_R_r_K, "slope"),
|
Z_lm_slope_R_r_K = Z_lm_R_r_K[[1]]$slope,
|
||||||
Z_lm_R_squared_R_r_K = map_dbl(Z_lm_R_r_K, "r_squared"),
|
Z_lm_R_squared_R_r_K = Z_lm_R_r_K[[1]]$r_squared,
|
||||||
Z_lm_Score_R_r_K = map_dbl(Z_lm_R_r_K, "score"),
|
Z_lm_Score_R_r_K = Z_lm_R_r_K[[1]]$score,
|
||||||
|
|
||||||
Z_lm_intercept_R_AUC_K = map_dbl(Z_lm_R_AUC_K, "intercept"),
|
Z_lm_intercept_R_AUC_K = Z_lm_R_AUC_K[[1]]$intercept,
|
||||||
Z_lm_slope_R_AUC_K = map_dbl(Z_lm_R_AUC_K, "slope"),
|
Z_lm_slope_R_AUC_K = Z_lm_R_AUC_K[[1]]$slope,
|
||||||
Z_lm_R_squared_R_AUC_K = map_dbl(Z_lm_R_AUC_K, "r_squared"),
|
Z_lm_R_squared_R_AUC_K = Z_lm_R_AUC_K[[1]]$r_squared,
|
||||||
Z_lm_Score_R_AUC_K = map_dbl(Z_lm_R_AUC_K, "score"),
|
Z_lm_Score_R_AUC_K = Z_lm_R_AUC_K[[1]]$score,
|
||||||
|
|
||||||
Z_lm_intercept_R_AUC_r = map_dbl(Z_lm_R_AUC_r, "intercept"),
|
Z_lm_intercept_R_AUC_r = Z_lm_R_AUC_r[[1]]$intercept,
|
||||||
Z_lm_slope_R_AUC_r = map_dbl(Z_lm_R_AUC_r, "slope"),
|
Z_lm_slope_R_AUC_r = Z_lm_R_AUC_r[[1]]$slope,
|
||||||
Z_lm_R_squared_R_AUC_r = map_dbl(Z_lm_R_AUC_r, "r_squared"),
|
Z_lm_R_squared_R_AUC_r = Z_lm_R_AUC_r[[1]]$r_squared,
|
||||||
Z_lm_Score_R_AUC_r = map_dbl(Z_lm_R_AUC_r, "score")
|
Z_lm_Score_R_AUC_r = Z_lm_R_AUC_r[[1]]$score
|
||||||
) %>%
|
) %>%
|
||||||
select(
|
select(
|
||||||
-lm_L, -lm_K, -lm_r, -lm_AUC, -Z_lm_K_L, -Z_lm_r_L, -Z_lm_R_AUC_L,
|
-lm_L, -lm_K, -lm_r, -lm_AUC, -Z_lm_K_L, -Z_lm_r_L, -Z_lm_R_AUC_L,
|
||||||
|
|||||||
Reference in New Issue
Block a user