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免疫相关 lncRNA 鉴定

作者

[编辑] ZCode (GLM) — AI 生成，独立 AI 复核

修改于

2026-11-05

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鉴定免疫相关 lncRNA 的方法是对 lncRNA 表达与免疫基因集做偏相关系数 + GSEA [1]。经典配图是双轴柱+线图：柱子展示每个癌种的免疫相关 lncRNA 数量（左 y 轴），线展示比例（右 y 轴）。

Example

ImmuneLncrnaPlot DEMO

Setup

  • 系统要求：跨平台（Linux/MacOS/Windows）

  • 编程语言：R

  • 依赖包： ggplot2; dplyr; scales

if (!requireNamespace("ggplot2", quietly = TRUE)) install.packages("ggplot2")
if (!requireNamespace("dplyr", quietly = TRUE)) install.packages("dplyr")
if (!requireNamespace("scales", quietly = TRUE)) install.packages("scales")

library(ggplot2)
library(dplyr)
library(scales)
sessioninfo::session_info("attached")
─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.6.2 (2026-10-29)
 os       Ubuntu 26.04.1 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  C.UTF-8
 ctype    C.UTF-8
 tz       UTC
 date     2026-11-05
 pandoc   3.7.0.2 @ /usr/bin/ (via rmarkdown)
 quarto   1.11.9 @ /usr/local/bin/quarto

─ Packages ───────────────────────────────────────────────────────────────────
 ! package * version    date (UTC) lib source
 P dplyr   * 1.2.1      2026-04-03 [?] RSPM
 P ggplot2 * 4.0.3.9000 2026-11-03 [?] Github (tidyverse/ggplot2@b638d65)
 P scales  * 1.4.0      2025-04-24 [?] RSPM

 [1] /home/runner/.cache/R/renv/library/Bizard-5140bdc6/linux-ubuntu-resolute/R-4.6/x86_64-pc-linux-gnu
 [2] /home/runner/work/_temp/Library
 [3] /opt/R/4.6.2/lib/R/library

 * ── Packages attached to the search path.
 P ── Loaded and on-disk path mismatch.

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

Data Preparation

真实数据中，免疫相关 lncRNA 通过 ImmuLncRNA 算法（偏相关 + GSEA）逐癌种鉴定。我们模拟逐癌种的汇总输出：免疫相关 lncRNA 数量与 lncRNA 总数，比例由此推导。

set.seed(1801)
cancers <- c("ACC", "BLCA", "BRCA", "CESC", "CHOL", "COAD", "ESCA", "GBM",
             "HNSC", "KICH", "KIRC", "KIRP", "LGG", "LIHC", "LUAD", "LUSC")
n_lnc_total <- sample(200:600, length(cancers))
n_immune    <- round(n_lnc_total * runif(length(cancers), 0.08, 0.35))

df <- data.frame(cancer = cancers,
                 total = n_lnc_total,
                 immune = n_immune) |>
  mutate(prop = immune / total)
head(df)
  cancer total immune       prop
1    ACC   273     86 0.31501832
2   BLCA   417     48 0.11510791
3   BRCA   555     67 0.12072072
4   CESC   268     72 0.26865672
5   CHOL   221     69 0.31221719
6   COAD   484     46 0.09504132

Visualization

1. 双轴柱+线图

max_count <- max(df$immune)
max_prop  <- max(df$prop)

ggplot(df, aes(cancer, immune)) +
  geom_col(fill = "#445EAD", width = 0.65) +
  geom_line(aes(cancer, prop * max_count / max_prop, group = 1),
            colour = "#B2182B", linewidth = 0.8) +
  geom_point(aes(cancer, prop * max_count / max_prop),
             colour = "#B2182B", size = 2) +
  scale_y_continuous(
    name = "Number of immune-related lncRNAs",
    sec.axis = sec_axis(~ . * max_prop / max_count,
                        name = "Proportion",
                        labels = percent)) +
    labs(title = "Immune-related lncRNAs across cancer types") +
  theme_classic(base_size = 11) +
  theme(axis.text.x = element_text(angle = 45, hjust = 1),
        axis.title.y.left = element_text(colour = "#445EAD"),
        axis.title.y.right = element_text(colour = "#B2182B"))
图 1: 双轴图：柱 = 免疫相关 lncRNA 数量（左），线 = 免疫相关 lncRNA 比例（右），逐癌种。
提示

Practice tips

  • 缩放因子 max_count / max_prop 将两个 y 轴对齐，使线落在柱的范围之内；可调整以避免视觉杂乱。
  • 两个 y 轴标题的颜色分别与柱和线的颜色匹配——读者本能地将轴标题颜色与对应图层匹配。
  • 参考工作流使用 ImmuLncRNA 包（偏相关 + GSEA）；双轴图是其输出的总结可视化。

Application

免疫相关 lncRNA 鉴定是免疫 lncRNA 生物标志物研究的第一步；双轴图跨癌种比较产出效率。

Reference

[1] Xiaofan Lu, et al. FigureYa: A Standardized Visualization Framework for Enhancing Biomedical Data Interpretation and Research Efficiency. iMetaMed. 2025. doi:10.1002/imm3.70005