# Load required libraries
pacman::p_load(pacman, tidyverse, tidyr, dplyr, readr, grid, gridExtra, ggplot2, RColorBrewer)
# Display colour choices, used to pick suitable colour schemes
#display.brewer.all()
# Load the 7 CSV files
emotional_recognition <- read_csv("emotional_recognition_corrected.csv", col_types = cols(
Recognized_Emotion = col_character(),
Happy_Target = col_double(),
Sad_Target = col_double(),
Angry_Target = col_double()
))
birth_characteristics_hospital <- read_csv("birth_characteristics_hospital_corrected.csv",
col_types = cols(.default = col_double(),
Hospital = col_character()
))
multi_feature_ttests <- read_csv("multi_feature_ttests_corrected.csv", col_types = cols(
Group = col_character(),
Latency_Window = col_character(),
Stimulus_Type = col_character(),
Stimulus = col_character(),
Electrode = col_character(),
t_value = col_double(),
significance = col_character(),
mean = col_double(),
SD = col_double(),
CI_lower = col_double(),
CI_upper = col_double()
))
oddball_ttests <- read_csv("oddball_ttests_corrected.csv", col_types = cols(
Group = col_character(),
Latency_Window = col_character(),
Electrode = col_character(),
t_value = col_double(),
significance = col_character(),
mean = col_double(),
SD = col_double(),
CI_lower = col_double(),
CI_upper = col_double()
))
interaction_effects <- read_csv("interaction_effects_corrected.csv", col_types = cols(
Latency_Window = col_character(),
Stimulus = col_character(),
Electrode1 = col_character(),
Mean1 = col_double(),
Electrode2 = col_character(),
Mean2 = col_double(),
p_value = col_double()
))
rm_anova_pvalues <- read_csv("rm_anova_pvalues_corrected.csv", col_types = cols(
Latency_Window = col_character(),
Stimulus1 = col_character(),
Stimulus2 = col_character(),
p_value = col_double()
))
rm_ancova_pvalues <- read_csv("rm_ancova_pvalues_corrected.csv", col_types = cols(
Latency_Window = col_character(),
Stimulus1 = col_character(),
Stimulus2 = col_character(),
p_value = col_double()
))
# Subtitle: Study Name
Subtitle <- "Clinical Trial: Repeated Parental Singing During Kangaroo Care Improved Neural Processing of Speech Sound Changes in Preterm Infants at Term Age"
# Viz 1: Emotional Recognition - Bar Plot
emotional_recognition_long <- emotional_recognition %>%
pivot_longer(cols = ends_with("_Target"), names_to = "Target", values_to = "Percentage") %>%
mutate(Target = gsub("_Target", "", Target))
ggplot(emotional_recognition_long, aes(x = Recognized_Emotion, y = Percentage, fill = Target)) +
geom_bar(stat = "identity", position = "stack", color = "black") +
scale_fill_brewer(palette = "Set1") +
labs(title = "Plot 1: Emotional Recognition Test Results",
subtitle = Subtitle,
x = "Recognised Emotion",
y = "Percentage (%)",
caption = "Source: Supplementary Table 1") +
theme_minimal() +
theme(plot.title = element_text(face = "bold", size = 14),
axis.text.x = element_text(angle = 45, hjust = 1),
legend.position = "top")
# Viz 2: Birth Characteristics by Hospital - Box Plots for Key Metrics
birth_metrics <- birth_characteristics_hospital %>%
select(Hospital, Gestational_weeks_mean, Weight_mean, Height_mean) %>%
pivot_longer(cols = c(Gestational_weeks_mean, Weight_mean, Height_mean),
names_to = "Metric", values_to = "Value")
ggplot(birth_metrics, aes(x = Hospital, y = Value, fill = Hospital)) +
geom_boxplot(alpha = 0.7) +
facet_wrap(~ Metric, scales = "free_y",
labeller = labeller(Metric = c(Gestational_weeks_mean = "Gestational Weeks",
Weight_mean = "Weight (g)",
Height_mean = "Height (cm)"))) +
scale_fill_manual(values = c("#FFB6C1", "#87CEEB")) +
labs(title = "Plot 2: Birth Characteristics by Hospital",
subtitle = Subtitle,
x = "Hospital",
y = "Value",
caption = "Source: Supplementary Table 2") +
theme_light() +
theme(plot.title = element_text(face = "bold", size = 14),
legend.position = "none")
# Viz 3: Multi-feature T-tests - Line Plot with Error Bars (Happy Stimulus, 200-300 ms)
multi_feature_subset <- multi_feature_ttests %>%
filter(Stimulus == "Happy", Latency_Window == "200-300 ms")
ggplot(multi_feature_subset, aes(x = Electrode, y = mean, color = Group)) +
geom_line(aes(group = Group), size = 1) +
geom_point(size = 3) +
geom_errorbar(aes(ymin = CI_lower, ymax = CI_upper), width = 0.2, size = 0.8) +
scale_color_manual(values = c("#FF4500", "#4682B4")) +
labs(title = "Plot 3: Mean Responses for Happy Stimulus (200-300 ms)",
subtitle = Subtitle,
x = "Electrode",
y = "Mean Response",
caption = "Source: Supplementary Table 3a") +
theme_classic() +
theme(plot.title = element_text(face = "bold", size = 14))
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
# Viz 4: Oddball T-tests - Line Plot with Error Bars (200-300 ms)
oddball_subset <- oddball_ttests %>%
filter(Latency_Window == "200-300 ms")
ggplot(oddball_subset, aes(x = Electrode, y = mean, color = Group)) +
geom_line(aes(group = Group), size = 1) +
geom_point(size = 3) +
geom_errorbar(aes(ymin = CI_lower, ymax = CI_upper), width = 0.2, size = 0.8) +
scale_color_manual(values = c("#FFD700", "#6A5ACD")) +
labs(title = "Plot 4: Mean Responses in Oddball Paradigm (200-300 ms)",
subtitle = Subtitle,
x = "Electrode",
y = "Mean Response",
caption = "Source: Supplementary Table 3b") +
theme_classic() +
theme(plot.title = element_text(face = "bold", size = 14))
# Viz 5: Interaction Effects - Grouped Bar Plot
interaction_effects_long <- interaction_effects %>%
pivot_longer(cols = c(Mean1, Mean2), names_to = "Electrode_Type", values_to = "Mean") %>%
mutate(Electrode = if_else(Electrode_Type == "Mean1", Electrode1, Electrode2))
ggplot(interaction_effects_long, aes(x = Electrode, y = Mean, fill = Stimulus)) +
geom_bar(stat = "identity", position = "dodge", color = "black") +
scale_fill_brewer(palette = "Dark2") +
labs(title = "Plot 5: Interaction Effects: Mean Responses by Electrode and Stimulus",
subtitle = Subtitle,
x = "Electrode",
y = "Mean Response",
caption = "Source: Supplementary Table 4") +
theme_minimal() +
theme(plot.title = element_text(face = "bold", size = 14),
legend.position = "top")
# Viz 6: RM ANOVA P-values - Heatmap
ggplot(rm_anova_pvalues, aes(x = Stimulus2, y = Stimulus1, fill = p_value)) +
geom_tile(color = "white") +
scale_fill_gradient(low = "#CC3300", high = "#CCCCCC", limits = c(0, 0.05)) +
facet_wrap(~ Latency_Window) +
labs(title = "Plot 6: RM ANOVA P-values for Stimulus Main Effect",
subtitle = Subtitle,
x = "Stimulus 2",
y = "Stimulus 1",
caption = "Source: Supplementary Table 6") +
theme_minimal() +
theme(plot.title = element_text(face = "bold", size = 14),
axis.text.x = element_text(angle = 45, hjust = 1))
# Viz 7: RM ANCOVA P-values - Heatmap
ggplot(rm_ancova_pvalues, aes(x = Stimulus2, y = Stimulus1, fill = p_value)) +
geom_tile(color = "white") +
scale_fill_gradient(low = "#0033FF", high = "#CCCCCC", limits = c(0, 0.05)) +
labs(title = "Plot 7: RM ANCOVA P-values for Stimulus Main Effect (550-650 ms)",
subtitle = Subtitle,
x = "Stimulus 2",
y = "Stimulus 1",
caption = "Source: Supplementary Table 7") +
theme_minimal() +
theme(plot.title = element_text(face = "bold", size = 14),
axis.text.x = element_text(angle = 45, hjust = 1))
