如何在haploNet单倍型网络{pegas}中绘制饼图 [英] How to plot Pie charts in haploNet Haplotype Networks {pegas}
问题描述
我正在尝试使用{pegas}的haploNet函数绘制单倍型网络，但是我很难将来自不同种群的相同单倍型放在同一饼图中.我可以使用以下脚本构建单倍型网络:
I'm trying to use haploNet function of {pegas} to plot a haplotype network, but i`m having trouble putting equal haplotypes from different populations in a same piechart. I can build a haplotype net with the following script:
x <- read.dna(file="x.fas",format="fasta")
h <- haplotype(x)
net <- haploNet(h)
plot(net)
我想在dnabin数据中设置每个分类单元的原始种群的标签，这样我可以在生成的网络中使用不同颜色(来自不同种群的单倍型)的饼图.我也想删除生成的单倍型网络中的重叠圆圈.
I'd like to set in the dnabin data the label of the original population of each taxa, so i could have piecharts of different colors (of haplotypes from different populations) in the resulting network. I'd like also to remove overlapping circles in the resulting haplotype network.
感谢您的帮助！
一个例子:
> data(woodmouse)
> x <- woodmouse[sample(15, size = 110, replace = TRUE), ]
> h <- haplotype(x)
> net <- haploNet(h)
> plot(net, size=attr(net, "freq"), scale.ratio = 2, cex = 0.8)
此脚本用于使用{pegas}构建单倍型网络.较大的圆圈代表更多的某种单倍型.我想知道如何在dnabin矩阵中设置单倍型的起源，以便它们在网络中以不同的颜色显示.
This script is used to build an haplotype network using {pegas}. The bigger circles represent much more haplotypes of some type. I`d like to know how I could set in the dnabin matrix the origin of the haplotypes, so they would appear with different colors in the network.
推荐答案
好，尝试从您的示例中弄清楚.看来您所拥有的种群是15个种群，每个种群有3-13个样本.
Ok, trying to make sense from your example. It appears the populations you have are 15 populations with anywhere from 3-13 samples per population.
table(rownames(x))
# No0906S No0908S No0909S No0910S No0912S No0913S No1007S
# 10 8 6 3 3 7 6
# No1103S No1114S No1202S No1206S No1208S No304 No305
# 4 13 9 6 9 13 7
# No306
# 6
运行haplotype(x)时，(毫不奇怪)您将获得15个单倍型，这表示从人口到单倍型的1:1映射.我们可以使用
When you run haplotype(x), you get (unsurprisingly) 15 haplotypes representing a 1:1 mapping from population to haplotype. We can create a table showing the relationship between the populations and haplotypes with
ind.hap<-with(
stack(setNames(attr(h, "index"), rownames(h))),
table(hap=ind, pop=rownames(x)[values])
)
ind.hap[1:10, 1:9] #print just a chunk
# pop
# hap No0906S No0908S No0909S No0910S No0912S No0913S No1007S No1103S No1114S
# I 0 0 0 0 0 0 0 0 0
# II 0 0 0 0 0 0 6 0 0
# III 0 0 0 0 0 0 0 4 0
# IV 10 0 0 0 0 0 0 0 0
# IX 0 0 0 0 0 0 0 0 0
# V 0 0 6 0 0 0 0 0 0
# VI 0 0 0 0 0 0 0 0 0
# VII 0 0 0 0 0 7 0 0 0
# VIII 0 0 0 0 0 0 0 0 13
# X 0 0 0 0 0 0 0 0 0
我们可以在绘制过程中使用此表在每个节点上绘制图片字符.
We can use this table during plotting to draw pic chars at each of the nodes.
plot(net, size=attr(net, "freq"), scale.ratio = 2, cex = 0.8, pie=ind.hap)
legend(50,50, colnames(ind.hap), col=rainbow(ncol(ind.hap)), pch=20)
为了更好地展示饼图，我们可以为每个样本分配不正确的总体
To better show off the pie charts, we can assign incorrect populations to each of the samples
wrong.pop<-rep(letters[1:5], each=22)
ind.hap2<-with(
stack(setNames(attr(h, "index"), rownames(h))),
table(hap=ind, pop=wrong.pop[values])
)
plot(net, size=attr(net, "freq"), scale.ratio = 2, cex = 0.8, pie=ind.hap2)
legend(50,50, colnames(ind.hap2), col=rainbow(ncol(ind.hap2)), pch=20)
在这里您可以看到每种单倍型都有更多的多样性，因为我们用人工名称错误地标记了种群，因此它们不会像簇一样好.
Here you can see we have more diversity at each haplotype because we've incorrectly labeled the populations with artificial names so they don't clump as nicely.
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