订单数据在ggplot2中绘制barplot [英] order data to plot barplot in ggplot2

问题描述

我需要建立我的数据的barplot，显示不同样本中的细菌相对丰度（每个列在总数据集中总和应为1）。

子集我的数据：

 > mydata 
 
 
 Taxon CD6 CD1 CD12 
 Actinomycetaceae; g__Actinomyces 0.031960309 0.066683743 0.045638509 
 Coriobacteriaceae; g__Atopobium 0.018691589 0.003244536 0.00447774 
棒状杆菌科; g__棒状杆菌0.001846083 0.006403689 0.000516662 
 Micrococcaceae; g__Rothia 0.001730703 0.000426913 0.001894429 
 Porphyromonadaceae; g__Porphyromonas 0.073497173 0.065915301 0.175406872 
  

（CD6，CD1，CD12），其中y值是细菌种类的相对丰度（Taxon列）。

I认为（但我不确定）我的数据格式不适合做这个情节，因为我没有一个变量来组合，就像我发现的例子一样......

ggplot（data）+ geom_bar（aes（x = revision，y = added），stat =identity，fill =white，color =black p>

有没有一种方法可以将数据排序为正确的inp ut到这个代码？
或者我该如何修改它？
Thanks！

解决方案

你想要这样的东西吗？

 ＃sample data 
 df < -  read.table（header = T，sep =，text = 
 Taxon CD6 CD1 CD12 
 Actinomycetaceae; g__Actinomyces 0.031960309 0.066683743 0.045638509 
 Coriobacteriaceae; g__Atopobium 0.018691589 0.003244536 0.00447774 
 Corynebacteriaceae; g__Corynebacterium 0.001846083 0.006403689 0.000516662 
 Micrococcaceae; g__Rothia 0.001730703 0.000426913 0.001894429 
 Porphyromonadaceae; g__Porphyromonas 0.073497173 0.065915301 0.175406872）
 
＃将宽数据格式转换为长格式
 require（reshape2）
 df.long < -  melt（df，id .vars =Taxon，
 measure.vars = grep（CD \\d +，names（df），val = T），
 variable.name =sample，
 value.name =value）
 
＃计算比例
 require（plyr）
 df.long<  -  ddply（df.long，。（sample）， transform，value = value / sum（value））
 
＃以id 
的顺序排列样本df.long $ sample<  -  reorder（df.long $ sample，as.numer ic（sub（CD，，df.long $ sample）））
 
＃plot using ggplot 
 require（ggplot2）
 ggplot（df.long，aes （x = sample，y = value，fill = Taxon））+ 
 geom_bar（stat =identity）+ 
 scale_fill_manual（values = scales :: hue_pal（h = c（0,360）+ 15，＃添加手动颜色
c = 100，
l = 65，
 h.start = 0，
 direction = 1）（length（levels（df $ Taxon））））） 
  

I need to build a barplot of my data, showing bacterial relative abundance in different samples (each column should sum to 1 in the complete dataset).

A subset of my data:

> mydata


Taxon   CD6 CD1 CD12
Actinomycetaceae;g__Actinomyces 0.031960309 0.066683743 0.045638509
Coriobacteriaceae;g__Atopobium  0.018691589 0.003244536 0.00447774
Corynebacteriaceae;g__Corynebacterium   0.001846083 0.006403689 0.000516662
Micrococcaceae;g__Rothia    0.001730703 0.000426913 0.001894429
Porphyromonadaceae;g__Porphyromonas 0.073497173 0.065915301 0.175406872

What I'd like to have is a bar for each sample (CD6, CD1, CD12), where the y values are the relative abundance of bacterial species (the Taxon column).

I think (but I'm not sure) my data format is not right to do the plot, since I don't have a variable to group by like in the examples I found...

ggplot(data) + geom_bar(aes(x=revision, y=added), stat="identity", fill="white", colour="black")

Is there a way to order my data making them right as input to this code? Or how can I modify it? Thanks!

解决方案

Do you want something like this?

# sample data
df <- read.table(header=T, sep=" ", text="
Taxon CD6 CD1 CD12
Actinomycetaceae;g__Actinomyces 0.031960309 0.066683743 0.045638509
Coriobacteriaceae;g__Atopobium 0.018691589 0.003244536 0.00447774
Corynebacteriaceae;g__Corynebacterium 0.001846083 0.006403689 0.000516662
Micrococcaceae;g__Rothia 0.001730703 0.000426913 0.001894429
Porphyromonadaceae;g__Porphyromonas 0.073497173 0.065915301 0.175406872")

# convert wide data format to long format
require(reshape2)
df.long <- melt(df, id.vars="Taxon",
                measure.vars=grep("CD\\d+", names(df), val=T),
                variable.name="sample",
                value.name="value")

# calculate proportions
require(plyr)
df.long <- ddply(df.long, .(sample), transform, value=value/sum(value))

# order samples by id     
df.long$sample <- reorder(df.long$sample, as.numeric(sub("CD", "", df.long$sample)))

# plot using ggplot
require(ggplot2)
ggplot(df.long, aes(x=sample, y=value, fill=Taxon)) + 
  geom_bar(stat="identity") +
  scale_fill_manual(values=scales::hue_pal(h = c(0, 360) + 15, # add manual colors
                                           c = 100, 
                                           l = 65, 
                                           h.start = 0, 
                                           direction = 1)(length(levels(df$Taxon))))

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