采用circlize包绘制Circos图-技术圈

本文采用circlize包自带的示例数据绘制Circos图，简要描述了circlize包的用法，以及几个常用参数的作用。

Circos图（圈图）功能

可展示的数据：基因密度、基因功能注释、CG含量、突变频谱、CNV分布、组蛋白修饰、甲基化密度、转座子与顺式调控元件分布等等；

组学可涉及：基因组、外显子组、甲基化组、ATAC-Seq和ChiP-Seq等组学等等；

复杂度可包括：多个样本、多个组织，多个时期的组学数据；

图的类型可涵盖：（复杂）热图、散点图、密度图、折线图、（堆积）柱状图、弦图等等，同时展现多种图形及其变化关系。

# 本计算机的R的版本：
.libPaths()

## [1] "C:/Program Files/R/R-4.0.4/library"     
## [2] "C:/Users/HP/Documents/R/win-library/4.0"

# R-4.0.3
# [1] "C:/Users/ACER/Documents/R/win-library/4.0"
# [2] "C:/Program Files/R/R-4.0.3/library" 

# 安装新的R包只会默认安装到上述路径中。

# 安装circlize包
options("repos" = c(CRAN="http://mirrors.tuna.tsinghua.edu.cn/CRAN/"))
if (! require(circlize)) {
  install.packages('circlize')
}

## Loading required package: circlize

## Warning: package 'circlize' was built under R version 4.0.5

## ========================================
## circlize version 0.4.12
## CRAN page: https://cran.r-project.org/package=circlize
## Github page: https://github.com/jokergoo/circlize
## Documentation: https://jokergoo.github.io/circlize_book/book/
## 
## If you use it in published research, please cite:
## Gu, Z. circlize implements and enhances circular visualization
##   in R. Bioinformatics 2014.
## 
## This message can be suppressed by:
##   suppressPackageStartupMessages(library(circlize))
## ========================================

library(circlize)

1 | 使用测试数据绘图

获取测试绘图的数据：

一般以bed格式给出，前三列一般是坐标，后面可以增加任意列作为注释。

函数generateRandomBed用于获取示例的bed数据

bed = generateRandomBed(nr = 200)
head(bed)

##    chr    start      end     value1
## 1 chr1  1265305 23689474 -0.3692290
## 2 chr1 33693147 34684697  0.1979085
## 3 chr1 46407775 50257809 -0.2200499
## 4 chr1 50933154 50945647 -0.1620185
## 5 chr1 53258978 54441031  1.2335410
## 6 chr1 59225767 66683215  0.2868235

绘制基因组(人类)，版本为hg38 ：

使用circos.initializeWithIdeogram函数，其参数species的帮助：

Abbreviations of species. e.g. hg19 for human, mm10 for mouse. If this value is specified, the function will download cytoBand.txt.gz from UCSC website automatically. If there is no cytoband for user’s species, it will keep on trying to download chromInfo file. Pass to read.cytoband or read.chromInfo.

circos.clear() # 绘图初始化
circos.initializeWithIdeogram(species = "hg38")

注意：后续的绘图函数都依赖于circos.initializeWithIdeogram

添加SNV、INDEL的信息，以点图展示，基于上面生成的bed数据：

circos.clear() # 绘图初始化
circos.initializeWithIdeogram(species = "hg38")
circos.genomicTrack(bed, 
                    panel.fun = function(region, value, ...) {
                      circos.genomicPoints(region, value, pch = 16, cex = 0.5, col = 1)})

添加CNV

circos.clear() # 绘图初始化
circos.initializeWithIdeogram(species = "hg38")
circos.genomicTrack(bed, 
                    panel.fun = function(region, value, ...) {
                      circos.genomicPoints(region, value, pch = 16, cex = 0.5, col = 1)})
circos.genomicTrack(bed, 
                    panel.fun = function(region, value, ...) {
                      circos.genomicRect(region, value, ytop.column = 1, ybottom = 0, 
                                         col = ifelse(value[[1]] > 0, "red", "green"), ...)
                      circos.lines(CELL_META$cell.xlim, c(0, 0), lty = 2, col = "#00000040")
})
# 大于阈值（例如0）即为红色柱子，否则为绿色柱子

示例数据绘图——高级

circos.clear()
circos.par("start.degree" = 90)
circos.par("gap.degree" = rep(c(2, 2), 12), ADD = TRUE)
circos.initializeWithIdeogram(species = "hg38", plotType = c("axis", "labels"))
text(0, 0, "Sample1", cex = 1)

# 添加SNV、INDEL的信息：
circos.genomicTrack(bed, 
                    panel.fun = function(region, value, ...) {
                      circos.genomicPoints(region, value, pch = 16, cex = 0.5, col = 1)})

# 添加CNV：
circos.genomicTrack(bed, 
                    panel.fun = function(region, value, ...) {
                      circos.genomicRect(region, value, ytop.column = 1, ybottom = 0, 
                                         col = ifelse(value[[1]] > 0, "red", "green"), ...)
                      circos.lines(CELL_META$cell.xlim, c(0, 0), lty = 2, col = "#00000040")
})

# 大于阈值（例如0）即为红色柱子，否则为绿色柱子

set.seed(50)

bed = generateRandomBed(nr = 200)
circos.clear()
circos.par("start.degree" = 90)
circos.par("gap.degree" = rep(c(2, 2), 12), ADD = TRUE)
circos.initializeWithIdeogram(species = "hg38", plotType = c("axis"))
text(0, 0, "Sample1", cex = 1)

# 染色体使用不同颜色的方框表示：
circos.track(ylim = c(0, 1), panel.fun = function(x, y) {
    chr = CELL_META$sector.index
    xlim = CELL_META$xlim
    ylim = CELL_META$ylim
    circos.rect(xlim[1], 0, xlim[2], 1, col = rand_color(24))
    circos.text(mean(xlim), mean(ylim), chr, cex = 0.6, col = "white",
        facing = "inside", niceFacing = TRUE)
}, track.height = 0.1, bg.border = NA)
# 添加SNV、INDEL的信息：
circos.genomicTrack(bed, 
                    panel.fun = function(region, value, ...) {
                      circos.genomicPoints(region, value, pch = 16, cex = 0.5, col = 1)})

# 添加CNV：
circos.genomicTrack(bed, 
                    panel.fun = function(region, value, ...) {
                      circos.genomicRect(region, value, ytop.column = 1, ybottom = 0, 
                                         col = ifelse(value[[1]] > 0, "red", "green"), ...)
                      circos.lines(CELL_META$cell.xlim, c(0, 0), lty = 2, col = "#00000040")
                    })
# 大于阈值（例如0）即为红色柱子，否则为绿色柱子

# bed（文件多样本value的合并）热图在内层：
circos.clear()
circos.initializeWithIdeogram()
bed = generateRandomBed(nr = 100, nc = 4)
col_fun = colorRamp2(c(-1, 0, 1), c("green", "black", "red"))
circos.genomicHeatmap(bed, col = col_fun, side = "inside", border = "white")

# bed（文件多样本value的合并）热图在外层：
circos.clear()
circos.initializeWithIdeogram(plotType = NULL)
circos.genomicHeatmap(bed, col = col_fun, side = "outside",
    line_col = as.numeric(factor(bed[[1]])))
circos.genomicIdeogram()

# 加Label：
circos.clear()
circos.initializeWithIdeogram()
bed.1 = generateRandomBed(nr = 100, nc = 4)
circos.genomicHeatmap(bed.1, col = col_fun, side = "outside",
    line_col = as.numeric(factor(bed[[1]])))
bed.2 = generateRandomBed(nr = 50, fun = function(k) sample(letters, k, replace = TRUE))
bed.2[1, 4] = "aaaaa"
circos.genomicLabels(bed.2, labels.column = 4, side = "inside")
# circos.genomicIdeogram()

2 | 示例代码汇总

rm(list = ls())
set.seed(100)

bed = generateRandomBed(nr = 100)
col_fun = colorRamp2(c(-1, 0, 1), c("green", "black", "red"))
# col_fun = colorRamp2(c(-1, 0, 1), c("navy", "grey", "firebrick3"))

circos.clear()

#pdf("./Circos.hg38.pdf")


circos.par("start.degree" = 90)
circos.par("gap.degree" = rep(c(2, 2), 12), ADD = TRUE)
circos.initializeWithIdeogram(species = "hg38", plotType = c("axis"))
text(0, 0, "Sample1", cex = 1)

####### 染色体使用不同颜色的方框表示：
circos.track(ylim = c(0, 1), panel.fun = function(x, y) {
    chr = CELL_META$sector.index
    xlim = CELL_META$xlim
    ylim = CELL_META$ylim
    circos.rect(xlim[1], 0, xlim[2], 1, col = rand_color(24))
    circos.text(mean(xlim), mean(ylim), chr, cex = 0.6, col = "white",
        facing = "inside", niceFacing = TRUE)
}, track.height = 0.1, bg.border = NA)

####### 添加SNV、INDEL的信息：
circos.genomicTrack(bed, 
                    panel.fun = function(region, value, ...) {
                      circos.genomicPoints(region, value, pch = 16, cex = 0.5, col = 1)},
                    stack = F, track.height = 0.1)

####### 添加CNV：
circos.genomicTrack(bed, 
                    panel.fun = function(region, value, ...) {
                      circos.genomicRect(region, value, ytop.column = 1, ybottom = 0, 
                                         col = ifelse(value[[1]] > 0, "red", "green"), ...)
                      circos.lines(CELL_META$cell.xlim, c(0, 0), lty = 2, col = "#00000040")
                    }, stack = F, track.height = 0.1)
# 大于阈值（例如0）即为红色柱子，否则为绿色柱子

####### 热图：
bed.1 = generateRandomBed(nr = 70, nc = 4)
# bed.1 = bed.1[1:10, ]
circos.genomicHeatmap(bed.1, col = col_fun, side = "inside", border = "white",
                      connection_height = mm_h(2),heatmap_height = 0.1,
    line_col = as.numeric(factor(bed[[1]])))

####### Label
bed.2 = generateRandomBed(nr = 10, fun = function(k) sample(letters, k, replace = TRUE))
bed.2[1, 4] = "aaa"
bed.2$value1 = paste0("Gene_",bed.2$value1)
circos.genomicLabels(bed.2, labels.column = 4,connection_height = mm_h(2),labels_height =cm_h(1.0), side = "inside")
# circos.genomicIdeogram()
# dev.off()