Manhattan Plot for GWAS Results – Jie Hua’s Bioinformatics Notes

参考教程 / Reference Tutorials

思问 & StatisticVision. (2025, March 14). R语言绘图25|Nature曼哈顿图复现 [微信公众号]. R语言绘图25|Nature曼哈顿图复现. https://mp.weixin.qq.com/s/3YlnB3Nm85v3FxE8F67oDw

基本信息 / Basic Information

曼哈顿图（Manhattan Plot)是基因组范围内关联研究（GWAS）中常用的可视化工具，用于展示单核苷酸多态性（SNP）与表型之间的关联。它通过在x轴上绘制基因组位置，在y轴上绘制-log10(p-value)来显示每个SNP的显著性水平。

The Manhattan plot is a visualization tool commonly used in genome-wide association studies (GWAS) to display the association between single nucleotide polymorphisms (SNPs) and phenotypes. It shows the significance level of each SNP by plotting genomic position on the x-axis and -log10(p-value) on the y-axis.

曼哈顿图的特点 / Features of a Manhattan Plot

X轴：基因组的位置，按照染色体编号和物理位置排列，每条染色体用不同的颜色区分
X-axis: genomic position, arranged by chromosome number and physical position, with each chromosome distinguished by a different color
Y轴：用-log₁₀(p-value)表示SNPs的显著性水平，越高表示显著性水平越高
Y-axis: -log₁₀(p-value) represents the significance level of SNPs; the higher the value, the more significant
阈值线：图中与X轴平行的一条线，表示不同的显著性水平，分别对应p-value的某些值，比如p<5x10^-8
Threshold line: a line in the plot parallel to the x-axis, indicating different significance levels, which correspond to certain p-value values, such as p<5x10^-8
点: 每一个点表示一个SNPs，其高度表示显著性程度
Points: each point represents a SNP, and its height indicates the degree of significance

相关脚本 / Related Scripts

通过 Listing 1 加载了需要用到的的 R 包。

The required R packages are loaded via Listing 1.

Listing 1: Load required packages

library(ggplot2)
library(dplyr)

生成模拟数据

Generate simulated data

Code

set.seed(42)
data <- data.frame(
  SNP=paste0("rs",1:10000),
  CHR=rep(1:22, length.out=10000),
  BP=sample(1:1e6, 10000),
  P=runif(10000)
)

First 6 rows of the demo data
SNP	CHR	BP	P
rs1	1	61413	0.4715924
rs2	2	54425	0.5765097
rs3	3	623844	0.2229165
rs4	4	74362	0.3966966
rs5	5	46208	0.3641330
rs6	6	964632	0.6577111

计算-log₁₀(p-value)

Compute -log₁₀(p-value)

Code

data <- data %>%
  mutate(logP = -log10(P))

First 6 rows of the demo data
SNP	CHR	BP	P	logP
rs1	1	61413	0.4715924	0.3264332
rs2	2	54425	0.5765097	0.2391934
rs3	3	623844	0.2229165	0.6518579
rs4	4	74362	0.3966966	0.4015415
rs5	5	46208	0.3641330	0.4387400
rs6	6	964632	0.6577111	0.1819648

画图展示相关的数据

Plot the data

Code

ggplot(data, aes(x=BP, y=logP, color=as.factor(CHR)))+ 
  geom_point(alpha = 0.6, size = 1)+ 
  facet_grid(. ~ CHR, scales = "free_x", space = "free_x")+ 
  geom_hline(yintercept = -log10(5e-8), linetype = "dashed", color = "red")+ 
  labs(title = "Manhattan Plot",
       x = "Chromosome",
       y = "-log10(p-value)",
       color = "Chromosomes" ) + 
  theme_blog() + 
  theme(strip.text.x = element_blank(), 
        panel.spacing.x = unit(0.1, "lines"), 
        axis.text.x = element_blank(), 
        legend.position = "none")