trackview（r包）包绘制基因棒棒图

生信技能树

发布于 2025-02-05 13:20:43

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代码可运行

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代码可运行

关于基因棒棒图有很多包可以实现，搜集了一下，有10多个：

1、trackViewer（r包）：https://jianhong.github.io/trackViewer/articles/lollipopPlot.html

2、maftools（r包）：https://bioconductor.org/packages/devel/bioc/vignettes/maftools/inst/doc/maftools.html

3、GenVisR（r包）：https://github.com/griffithlab/GenVisR

4、proteinpaint（网页）：https://docs.gdc.cancer.gov/Data_Portal/Users_Guide/proteinpaint_lollipop/

5、G3viz（r包）：https://g3viz.github.io/g3viz/，https://github.com/g3viz/g3lollipop.js

6、lolliprot（r包）：https://github.com/vaporised/lolliprot

7、lollipops：https://github.com/pbnjay/lollipops, https://joiningdata.com/lollipops/index.html

8、muts-needle-plot：https://github.com/bbglab/muts-needle-plot

9、Mutplot（网页）：https://github.com/VivianBailey/Mutplot

10、ggplot2（r包）：https://stackoverflow.com/questions/77473777/adding-branches-to-ggplot-mutation-lollipop-plot

今天来学习第一个：trackViewer（r包）

官方教程：https://jianhong.github.io/trackViewer/articles/lollipopPlot.html

数据可以是甲基化或突变位点与注释数据。

先来一个简单的棒棒图：

rm(list=ls())

library(trackViewer)
SNP <- c(10, 12, 1400, 1402)
sample.gr <- GRanges("chr1", IRanges(SNP, width=1, names=paste0("snp", SNP)))
features <- GRanges("chr1", IRanges(c(1, 501, 1001), 
                                    width=c(120, 400, 405),
                                    names=paste0("block", 1:3)))

sample.gr
features

lolliplot(sample.gr, features)

这个图展示了样本中1号染色体上的4个SNP位点：

改变颜色

不同的block颜色不一样

## More SNPs
SNP <- c(10, 100, 105, 108, 400, 410, 420, 600, 700, 805, 840, 1400, 1402)
sample.gr <- GRanges("chr1", IRanges(SNP, width=1, names=paste0("snp", SNP)))
features <- GRanges("chr1", IRanges(c(1, 501, 1001), 
                                    width=c(120, 400, 405),
                                    names=paste0("block", 1:3)))
# 不同的block颜色不一样
features$fill <- c("#FF8833", "#51C6E6", "#DFA32D")
lolliplot(sample.gr, features)

改变棒棒的颜色：

sample.gr$color <- sample.int(6, length(SNP), replace=TRUE)
sample.gr$border <- sample(c("gray80", "gray30"), length(SNP), replace=TRUE)
sample.gr$alpha <- sample(100:255, length(SNP), replace = TRUE)/255
sample.gr
# GRanges object with 13 ranges and 3 metadata columns:
#   seqnames    ranges strand |     color      border     alpha
# <Rle> <IRanges>  <Rle> | <integer> <character> <numeric>
#   snp10     chr1        10      * |         4      gray30  0.494118
# snp100     chr1       100      * |         3      gray80  0.741176
# snp105     chr1       105      * |         1      gray80  0.470588
# snp108     chr1       108      * |         2      gray30  0.835294
# snp400     chr1       400      * |         5      gray30  0.984314
# ...      ...       ...    ... .       ...         ...       ...
# snp700     chr1       700      * |         3      gray30  0.811765
# snp805     chr1       805      * |         2      gray80  0.450980
# snp840     chr1       840      * |         5      gray30  0.847059
# snp1400     chr1      1400      * |         3      gray30  0.843137
# snp1402     chr1      1402      * |         4      gray30  0.921569
# -------
#   seqinfo: 1 sequence from an unspecified genome; no seqlengths

lolliplot(sample.gr, features)

圈圈中添加标签

可以通过设置以node.label.开头的元数据来逐个控制节点标签。对于每个节点标签，node.label.gp必须是一个列表，以控制节点标签的样式。也可以简单地使用node.label.col、node.label.cex、node.label.fontsize、node.label.fontfamily、node.label.fontface、node.label.font来分配节点标签属性。

sample.gr$node.label <- as.character(seq_along(sample.gr))
sample.gr$node.label.col <- 
  ifelse(sample.gr$alpha>0.5 | sample.gr$color==1, "white", "black")
sample.gr$node.label.cex <- sample.int(3, length(sample.gr), replace = TRUE)/2
# [1] 1.0 1.0 1.0 1.5 0.5 1.0 1.0 1.5 1.0 0.5 1.0 0.5 1.5

# 绘图
lolliplot(sample.gr, features)

改变图中block方框的高度

features$height <- c(0.02, 0.05, 0.08)
lolliplot(sample.gr, features)

同时绘制两个转录本的SNP情况

features.mul <- rep(features, 2)
features.mul$height[4:6] <- list(unit(1/8, "inches"), unit(0.5, "lines"), unit(.2, "char"))
features.mul$fill <- c("#FF8833", "#F9712A", "#DFA32D", "#51C6E6", "#009DDA", "#4B9CDF")
end(features.mul)[5] <- end(features.mul[5])+50
features.mul$featureLayerID <- paste("tx", rep(1:2, each=length(features)), sep="_")
# names(features.mul) <- paste(features.mul$featureLayerID, rep(1:length(features), 2), sep="_")
## One name per transcript
names(features.mul) <- features.mul$featureLayerID

# 
# GRanges object with 6 ranges and 3 metadata columns:
#   seqnames    ranges strand |        fill      height featureLayerID
# <Rle> <IRanges>  <Rle> | <character>      <list>    <character>
#   tx_1     chr1     1-120      * |     #FF8833        0.02           tx_1
#   tx_1     chr1   501-900      * |     #F9712A        0.05           tx_1
#   tx_1     chr1 1001-1405      * |     #DFA32D        0.08           tx_1
#   tx_2     chr1     1-120      * |     #51C6E6 0.125inches           tx_2
#   tx_2     chr1   501-950      * |     #009DDA    0.5lines           tx_2
#   tx_2     chr1 1001-1405      * |     #4B9CDF     0.2char           tx_2
#   -------
#   seqinfo: 1 sequence from an unspecified genome; no seqlengths

# 绘图
lolliplot(sample.gr, features.mul)

将同一个位点的多个SNP圈圈叠在一起

# Note: the score value is an integer less than 10
sample.gr$score <- sample.int(5, length(sample.gr), replace = TRUE)
# Try a score value greater than 10
sample.gr$score <- sample.int(15, length(sample.gr), replace=TRUE)
sample.gr$node.label <- as.character(sample.gr$score)
sample.gr

#Try a float numeric score
sample.gr$score <- runif(length(sample.gr))*10
sample.gr$node.label <- as.character(round(sample.gr$score, digits = 1))

pdf(file = "test1.pdf",width = 8,height = 4)
lolliplot(sample.gr, features, lollipop_style_switch_limit=15, yaxis=FALSE)
dev.off()