如何用未排序的x轴(格子)绘制条形图

问题描述

我的代码如下所示:

read.table("GO.txt",header=T,sep=',')->go
library(lattice)
barchart(go[,1]~go[,2],horiz=F,ylim=c(30,29666),
layout=c(1,1),stack=F,
auto.key=list(space='right'),
ylab="Yes",
scales=list(x=list(rot=45),y=list(log = T)))

但是，我不想绘制带有x排序的图表，该怎么办?格对我不需要的数据进行了排序.

However, I don't want to plot a chart with sorted x, what should I do?The lattice sorted my data which I don't need.

数据:

    number_of_A-Unigene Class   Ontology
    45  biological adhesion biological_process
    5328    biological regulation   biological_process
    8   carbon utilization  biological_process
    6   cell killing    biological_process
    119 cell proliferation  biological_process
    3248    cellular component organization or biogenesis   biological_process
    16594   cellular process    biological_process
    244 death   biological_process
    4354    developmental process   biological_process
    3547    establishment of localization   biological_process
    917 growth  biological_process
    429 immune system process   biological_process
    3716    localization    biological_process
    30  locomotion  biological_process
    15726   metabolic process   biological_process
    4182    multicellular organismal process    biological_process
    1673    multi-organism process  biological_process
    877 negative regulation of biological process   biological_process
    10  nitrogen utilization    biological_process
    11  pigmentation    biological_process
    640 positive regulation of biological process   biological_process
    4808    regulation of biological process    biological_process
    2462    reproduction    biological_process
    2437    reproductive process    biological_process
    7812    response to stimulus    biological_process
    190 rhythmic process    biological_process
    2001    signaling   biological_process
    2   sulfur utilization  biological_process
    44  viral reproduction  biological_process
    19852   cell    cellular_component
    1763    cell junction   cellular_component
    19852   cell part   cellular_component
    31  extracellular matrix    cellular_component
    9   extracellular matrix part   cellular_component
    686 extracellular region    cellular_component
    30  extracellular region part   cellular_component
    3698    macromolecular complex  cellular_component
    9829    membrane    cellular_component
    3432    membrane part   cellular_component
    1439    membrane-enclosed lumen cellular_component
    15252   organelle   cellular_component
    6024    organelle part  cellular_component
    1753    symplast    cellular_component
    216 antioxidant activity    molecular_function
    15917   binding molecular_function
    15103   catalytic activity  molecular_function
    2   channel regulator activity  molecular_function
    433 electron carrier activity   molecular_function
    319 enzyme regulator activity   molecular_function
    8   metallochaperone activity   molecular_function
    522 molecular transducer activity   molecular_function
    708 nucleic acid binding transcription factor activity  molecular_function
    26  nutrient reservoir activity molecular_function
    102 protein binding transcription factor activity   molecular_function
    6   protein tag molecular_function
    613 receptor activity   molecular_function
    1039    structural molecule activity    molecular_function

5个翻译调节子的活性Molecular_function2478转运蛋白的活动分子功能

5 translation regulator activity molecular_function2478 transporter activity molecular_function

推荐答案

格"采用因子变量并将其按默认(字母顺序)排列.您可以更改顺序.也许:

"Lattice" took your factor variables and arranged them in default (alphabetical) order. You can change the order. Perhaps:

go[,2] <- factor( go[,2] unique(as.character(go[,2])) )

这应该将级别设置为与您在分页浏览时第一次出现的顺序相同.另一个等效项(尽管更像巴洛克式)是:

This should set the levels in the same order as they would first appear if you were paging through them. Another equivalent, although more Baroque, assignment would be:

go[,2] <- factor( go[,2] as.character( go[,2][!duplicated(go[,2])]) )

然后做你的情节. (我没有尝试输入您的数据.它们看起来太乱了.嗯，实际上，我确实用制表符作为分隔符给了它一个镜头.如果它们曾经有制表符，那么它们会丢失，并且元素数量不定如果空格是分隔符.)

Then do your plot. (I did not attempt to input your data. They looked to be too messy. Well, actually I did give it a shot with tabs as the separator. If they once had tabs. then they lost them, and there are variable numbers of elements if white-space is the separator.)

使用重复问题中的数据，标签未排序:

Using the data in the duplicate question the labels are not sorted:

go[[2]] <- factor(go[[2]], levels=unique(as.character(go[[2]])))

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