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R绘图|时间热图

小汪Waud

发布于 2023-10-24 11:01:50

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在徐凌老师的 Nat Com 文章 Genome-resolved metagenomics reveals role of iron metabolism in drought-induced rhizosphere microbiome dynamics 中有这么一张补充图，介绍了本研究中涉及到的处理和取样的时间线。

这种图通常被称为时间热图或时间线图，结合了颜色块、标签和标记，我们按照以下步骤进行绘图：

数据准备：整理你的数据，确保每个时间点的数据都在正确的位置。
确定颜色：为不同的部分如Water applied/No water applied和不同Omics选择颜色。
绘制基础图形：首先，绘制一个时间线图形，区分“Control”和“Drought”。
添加颜色块：根据数据在相应的时间点添加颜色块。
添加标记：如红点和绿点，表示“Metagenome”和“16S rRNA amplicon seq”等。
添加图例：确保图例清晰，与图中使用的颜色和标记一致。
优化和调整。

下面我们尝试用R复现此图

1生成示例数据

data <- data.frame(
  Category = c(rep("Control", 18), rep("Drought", 18)),
  TimePoint = rep(paste0("TP", 0:17), 2),
  Water = c(rep("Water applied", 18), rep("No water applied", 5), rep("Water applied", 13)),
  Metagenome = c(rep(1, 9), rep(NA, 9), rep(NA, 5), rep(1, 13)),
  Transcriptome = c(rep(NA, 4), rep(1, 5), rep(NA, 9), rep(NA, 5), rep(1, 4), rep(NA, 9))
)

# 示例数据前六行
  Category TimePoint         Water Metagenome Transcriptome
1  Control       TP0 Water applied          1            NA
2  Control       TP1 Water applied          1            NA
3  Control       TP2 Water applied          1            NA
4  Control       TP3 Water applied          1            NA
5  Control       TP4 Water applied          1             1
6  Control       TP5 Water applied          1             1

2作图

library(ggplot2)

# 将TimePoint转换为有序因子
data$TimePoint <- factor(data$TimePoint, levels = paste0("TP", 0:17))

# 预定义颜色和其他属性
fill_colors <- c("Water applied" = "#7BAF8A", "No water applied" = "#D17F39")
color_values <- c("Metagenome" = "#9C281B", "Transcriptome" = "#343D5B")

# 使用ggplot2绘制图形
ggplot(data, aes(x = TimePoint, y = Category, fill = Water)) +
  geom_tile(color = "black", size = 0.5) +
  geom_point(data = subset(data, !is.na(Metagenome)), aes(color = "Metagenome"), size = 5,
             position = position_nudge(y = 0)) +
  geom_point(data = subset(data, !is.na(Transcriptome)), aes(color = "Transcriptome"), size = 5,
             position = position_nudge(y = -0.1)) +
  scale_fill_manual(values = fill_colors) +
  scale_color_manual(values = color_values) +
  guides(fill = guide_legend(override.aes = list(color = NA)))+
  labs(title = "Time point (in weeks)", fill = "", color = "", x = NULL) +
  theme_minimal() +
  theme(
    axis.title.y = element_blank(),
    panel.grid.major = element_blank(),
    axis.line.x = element_blank(),
    axis.text.x = element_text(face = "bold", size = 9,vjust = 12),
    axis.text.y = element_text(face = "bold", size = 10),
    plot.title = element_text(face = "bold", hjust = 0.5,vjust = -5))