图1 | 滩涂潮间带沉积物中病毒和微生物的概述。
c 潮间带沉积物中溶菌性和溶原性病毒的相对比例。箱线图显示了不同生活方式病毒的相对比例差异。箱线图中的点代表每个采样区域八个样本的平均值。箱体的中线表示12个采样区域的中位值。箱体的上下边界代表四分位范围，其中下边界对应第一个四分位数，上边界对应第三个四分位数。须线表示在第一个和第三个四分位数范围的1.5倍内的最低和最高值。差异的统计显著性使用双尾t检验确定。
以下是作图代码：
# Load necessary libraries
library(geojsonsf) # For handling GeoJSON data
library(sf) # For simple feature support for vector data
library(ggplot2) # For creating plots
library(RColorBrewer) # For color palettes
library(ggspatial) # For spatial data visualization
library(cowplot) # For combining plots
library(tidyverse) # For data manipulation and visualization
library(scales) # For scaling functions
library(ggsci) # For scientific journal and sci-fi themed color palettes
library(ggforce) # For additional ggplot2 functionality
library(reshape2) # For data reshaping
library(dplyr) # For data manipulation
library(readxl) # For reading Excel files
library(ggpubr) # For publication-ready plots
library(vegan) # For ecological data analysis
library(ggpmisc) # For adding mathematical annotations to ggplot2
# Read data from an Excel file
data <- read_excel("./raw_data_for_figure1/Fig.1c.xlsx")
# Set the factor levels for the 'letter' column
data$letter = factor(data$letter, levels = c("Lytic", "Lysogenic"))
# Create a violin plot with boxplot and jittered points
ggplot(data, aes(x = letter, y = ratio)) +
geom_violin(aes(fill = letter), trim = FALSE, width = 0.32, alpha = 0.9, size = 0.15) + # Violin plot
geom_boxplot(width = 0.18, size = 0.15) + # Boxplot
labs(x = "", y = "Relative proportion (%)") + # Axis labels
geom_jitter(aes(x = letter, y = ratio, fill = letter), shape = 21, stroke = 0.15, size = 0.65,
position = position_jitterdodge(jitter.width = 0.4), alpha = 0.8) + # Jittered points
scale_fill_manual(values = c("#7AC5CD", "#FF9B64")) + # Custom fill colors
theme(axis.line = element_line(color = "black")) + # Axis line color
theme_test() + # Apply test theme
theme(panel.grid.major = element_blank(), # Remove major grid lines
panel.grid.minor = element_blank(), # Remove minor grid lines
axis.title = element_text(size = 6.5), # Axis title text size
axis.ticks = element_line(size = 0.3), # Axis ticks line size
axis.ticks.length = unit(0.04, "cm"), # Axis ticks length
axis.text.x = element_text(hjust = 0.5, size = 6, color = 'black'), # X-axis text properties
axis.text.y = element_text(size = 6, color = 'black'), # Y-axis text properties
panel.border = element_rect(size = 0.35)) + # Panel border size
ylim(0, 100) + # Y-axis limits
theme(legend.position = "none") # Remove legend
作图结果：
image.png
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