扩散映射图

作者

[编辑] 郑虎;

[审核] .

修改于

2026-01-27

注记

Hiplot 网站

本页面为 Hiplot Diffusion Map 插件的源码版本教程，您也可以使用 Hiplot 网站实现无代码绘图，更多信息请查看以下链接:

https://hiplot.cn/basic/diffusion-map?lang=zh_cn

扩散映射（diffusion-map）是一种非线性降维算法，可以用于可视化发育轨迹。

环境配置

  • 系统: Cross-platform (Linux/MacOS/Windows)

  • 编程语言: R

  • 依赖包: data.table; jsonlite; destiny; ggplotify; scatterplot3d; ggpubr

# 安装包
if (!requireNamespace("data.table", quietly = TRUE)) {
  install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
  install.packages("jsonlite")
}
if (!requireNamespace("destiny", quietly = TRUE)) {
  install.packages("https://github.com/theislab/destiny/archive/refs/tags/v3.1.1.tar.gz")
}
if (!requireNamespace("ggplotify", quietly = TRUE)) {
  install.packages("ggplotify")
}
if (!requireNamespace("scatterplot3d", quietly = TRUE)) {
  install.packages("scatterplot3d")
}
if (!requireNamespace("ggpubr", quietly = TRUE)) {
  install.packages("ggpubr")
}

# 加载包
library(data.table)
library(jsonlite)
library(destiny)
library(ggplotify)
library(scatterplot3d)
library(ggpubr)
sessioninfo::session_info("attached")
─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.5.2 (2025-10-31)
 os       Ubuntu 24.04.3 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  C.UTF-8
 ctype    C.UTF-8
 tz       UTC
 date     2026-01-28
 pandoc   3.1.3 @ /usr/bin/ (via rmarkdown)
 quarto   1.8.27 @ /usr/local/bin/quarto

─ Packages ───────────────────────────────────────────────────────────────────
 package       * version date (UTC) lib source
 data.table    * 1.18.0  2025-12-24 [1] RSPM
 destiny       * 3.25.0  2025-11-06 [1] Github (theislab/destiny@8cc0bff)
 ggplot2       * 4.0.1   2025-11-14 [1] RSPM
 ggplotify     * 0.1.3   2025-09-20 [1] RSPM
 ggpubr        * 0.6.2   2025-10-17 [1] RSPM
 jsonlite      * 2.0.0   2025-03-27 [1] RSPM
 scatterplot3d * 0.3-44  2023-05-05 [1] RSPM

 [1] /home/runner/work/_temp/Library
 [2] /opt/R/4.5.2/lib/R/site-library
 [3] /opt/R/4.5.2/lib/R/library
 * ── Packages attached to the search path.

──────────────────────────────────────────────────────────────────────────────

数据准备

# 加载数据
data1 <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/diffusion-map/data.json")$exampleData[[1]]$textarea[[1]])
data1 <- as.data.frame(data1)
data2 <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/diffusion-map/data.json")$exampleData[[1]]$textarea[[2]])
data2 <- as.data.frame(data2)

# 整理数据格式
sample.info <- data2
rownames(data1) <- data1[, 1]
data1 <- as.matrix(data1[, -1])
## tsne
set.seed(123)
dm_info <- DiffusionMap(t(data1))
dm_info <- cbind(DC1 = dm_info$DC1, DC2 = dm_info$DC2, DC3 = dm_info$DC3)
dm_data <- data.frame(
  sample = colnames(data1),
  dm_info
)

colorBy <- sample.info[match(colnames(data1), sample.info[, 1]), "Group"]
colorBy <- factor(colorBy, level = colorBy[!duplicated(colorBy)])
dm_data$colorBy = colorBy

# 查看数据
head(dm_data)
   sample        DC1        DC2         DC3 colorBy
M1     M1 0.05059918 0.15203860 -0.06533168      G1
M2     M2 0.05030863 0.14435034 -0.06044277      G1
M3     M3 0.04271398 0.09273382 -0.02730427      G1
M4     M4 0.04680742 0.10425273 -0.03789962      G1
M5     M5 0.04971521 0.12786900 -0.05608321      G1
M6     M6 0.04840072 0.12728303 -0.05256815      G1

可视化

1. 2D

# 2D 扩散映射图
p <- ggscatter(data = dm_data,  x = "DC1", y = "DC2", color = "colorBy",
               size = 2, palette = "lancet", alpha = 1) +
  labs(color = "Group") +
  ggtitle("Diffusion Map") +
  scale_color_manual(values = c("#3B4992FF","#EE0000FF","#008B45FF")) +
  theme_classic() +
  theme(text = element_text(family = "Arial"),
        plot.title = element_text(size = 12,hjust = 0.5),
        axis.title = element_text(size = 12),
        axis.text = element_text(size = 10),
        axis.text.x = element_text(angle = 0, hjust = 0.5,vjust = 1),
        legend.position = "right",
        legend.direction = "vertical",
        legend.title = element_text(size = 10),
        legend.text = element_text(size = 10))

p
图 1: 2D 扩散映射图

2. 3D

# 3D 扩散映射图
group.color <- c("#3B4992FF","#EE0000FF","#008B45FF")
names(group.color) <- unique(dm_data$colorBy)
group.color <- group.color[!is.na(names(group.color))]
if (length(group.color) == 0) {
  group.color <- c(Default="black")
  dm_data$colorBy <- "Default"
}
p <- as.ggplot(function(){
  scatterplot3d(x = dm_data$DC1, y = dm_data$DC2, z = dm_data$DC3,
                color =  alpha(group.color[dm_data$colorBy], 1),
                xlim=c(min(dm_data$DC1), max(dm_data$DC1)),
                ylim=c(min(dm_data$DC2), max(dm_data$DC2)),
                zlim=c(min(dm_data$DC3), max(dm_data$DC3)),
                pch = 16, cex.symbols  = 0.6,
                scale.y = 0.8,
                xlab = "DC1", ylab = "DC2", zlab = "DC3",
                angle = 40,
                main = "Diffusion Map",
                col.axis = "#444444", col.grid = "#CCCCCC")
  legend("right", legend = names(group.color),
         col = alpha(group.color, 0.8), pch = 16)
    })
p <- p + theme_classic()

p
图 2: 3D 扩散映射图