英文:
Why I´m getting this error using barplot in Rstudio "incorrect number of names"?
问题
我正在尝试在Rstudio中为祖先制作一个条形图，但出现了错误"incorrect number of names"。这是我运行的代码：```{r}# Cargar los datosdatos <- read.table("admix.txt", header = TRUE)# Definir los nombres de las poblacionesPoblacion <- c("America","Europa","Eurasia","EurAm","Europasia")# Crear el gráfico de Admixturebarplot(t(as.matrix(datos[, -(1)])), col = rainbow(ncol(datos)-1),xlab = "Individuo", ylab = "Proporción", names.arg = Poblacion)
我的数据集：
...
origen 1 和 2 是使用混合得到的每个个体的祖先比例
我尝试了上面显示的代码，我期望得到这个：
<details><summary>英文:</summary>I´m trying to make a barplot for ancestry in Rstudio, an got the error "incorrect number of names"This is the code I run:```{r}# Cargar los datosdatos <- read.table("admix.txt", header = TRUE)# Definir los nombres de las poblacionesPoblacion <- c("America","Europa","Eurasia","EurAm","Europasia")# Crear el gráfico de Admixturebarplot(t(as.matrix(datos[, -(1)])), col = rainbow(ncol(datos)-1),xlab = "Individuo", ylab = "Proporción", names.arg = Poblacion)
My dataset:
Poblacion origen1 origen2America 0.006666 0.993334America 0.779961 0.220039America 0.427611 0.572389America 0.813640 0.186360America 0.652604 0.347396America 0.499865 0.500135America 0.290712 0.709288America 0.447847 0.552153America 0.840954 0.159046America 0.523092 0.476908America 0.000010 0.999990America 0.143286 0.856714America 0.472235 0.527765America 0.771131 0.228869America 0.511068 0.488932America 0.025474 0.974526America 0.000010 0.999990America 0.005296 0.994704America 0.685525 0.314475America 0.418856 0.581144America 0.653668 0.346332America 0.225173 0.774827America 0.383285 0.616715America 0.058886 0.941114America 0.009342 0.990658America 0.015007 0.984993America 0.002664 0.997336America 0.000010 0.999990America 0.145986 0.854014America 0.000010 0.999990America 0.015244 0.984756America 0.000010 0.999990America 0.000010 0.999990America 0.167392 0.832608America 0.640400 0.359600EurAm 0.000648 0.999352EurAm 0.255487 0.744513EurAm 0.000010 0.999990EurAm 0.450210 0.549790EurAm 0.000010 0.999990EurAm 0.546981 0.453019EurAm 0.484598 0.515402EurAm 0.086021 0.913979EurAm 0.285348 0.714652EurAm 0.031093 0.968907EurAm 0.069430 0.930570EurAm 0.037918 0.962082EurAm 0.022321 0.977679EurAm 0.320998 0.679002EurAm 0.106400 0.893600EurAm 0.048877 0.951123EurAm 0.182298 0.817702EurAm 0.031725 0.968275EurAm 0.312833 0.687167EurAm 0.457584 0.542416EurAm 0.054852 0.945148EurAm 0.553960 0.446040EurAm 0.002580 0.997420EurAm 0.025126 0.974874EurAm 0.999990 0.000010EurAm 0.000010 0.999990EurAm 0.147882 0.852118EurAm 0.000010 0.999990EurAm 0.221932 0.778068EurAm 0.181649 0.818351EurAm 0.595149 0.404851EurAm 0.681347 0.318653EurAm 0.000010 0.999990EurAm 0.702988 0.297012EurAm 0.000010 0.999990EurAm 0.002774 0.997226Eurasia 0.005494 0.994506Eurasia 0.000010 0.999990Eurasia 0.019013 0.980987Eurasia 0.019751 0.980249Eurasia 0.023125 0.976875Eurasia 0.335525 0.664475Eurasia 0.019229 0.980771Eurasia 0.028028 0.971972Eurasia 0.000010 0.999990Eurasia 0.667998 0.332002Eurasia 0.000010 0.999990Europa 0.021506 0.978494Europa 0.085614 0.914386Europa 0.002423 0.997577Europa 0.136019 0.863981Europa 0.000010 0.999990Europa 0.001705 0.998295Europa 0.008959 0.991041Europa 0.005611 0.994389Europa 0.000010 0.999990Europa 0.000010 0.999990Europa 0.011926 0.988074Europa 0.685324 0.314676Europa 0.026084 0.973916Europa 0.000010 0.999990Europa 0.016599 0.983401Europa 0.007035 0.992965Europa 0.132058 0.867942Europa 0.005673 0.994327Europa 0.000010 0.999990Europa 0.007433 0.992567Europa 0.022336 0.977664Europa 0.000010 0.999990Europa 0.076555 0.923445Europa 0.205925 0.794075Europa 0.023510 0.976490Europa 0.003213 0.996787Europa 0.000010 0.999990Europa 0.000010 0.999990Europa 0.020198 0.979802Europa 0.000010 0.999990Europa 0.174797 0.825203Europa 0.130237 0.869763Europa 0.128710 0.871290Europa 0.015761 0.984239Europa 0.016476 0.983524Europa 0.016811 0.983189Europa 0.000863 0.999137Europa 0.162520 0.837480Europa 0.000010 0.999990Europa 0.004684 0.995316Europa 0.019208 0.980792Europa 0.492487 0.507513Europa 0.000010 0.999990Europa 0.000010 0.999990Europa 0.015666 0.984334Europa 0.000010 0.999990Europa 0.018586 0.981414Europa 0.228070 0.771930Europa 0.054701 0.945299Europa 0.015723 0.984277Europa 0.000010 0.999990Europa 0.147377 0.852623Europa 0.000010 0.999990Europa 0.015433 0.984567Europa 0.194324 0.805676Europa 0.142146 0.857854Europa 0.181220 0.818780Europa 0.003677 0.996323Europa 0.355231 0.644769Europa 0.402608 0.597392Europa 0.067520 0.932480Europa 0.171952 0.828048Europa 0.014737 0.985263Europa 0.000010 0.999990Europa 0.003896 0.996104Europa 0.000010 0.999990Europa 0.795202 0.204798Europa 0.006578 0.993422Europa 0.021397 0.978603Europa 0.145587 0.854413Europa 0.062430 0.937570Europa 0.000010 0.999990Europa 0.012280 0.987720Europa 0.999990 0.000010Europa 0.020080 0.979920Europa 0.134631 0.865369Europasia 0.023057 0.976943Europasia 0.000010 0.999990Europasia 0.016871 0.983129Europasia 0.058525 0.941475
origen 1 and 2 are the proportions of ancestry for each individual obtained with admixture
I tried the code I showed you above,
I expect this:
答案1
得分: 0
由于您的 Poblacion 向量只有长度为5，barplot 不知道您希望 names.arg 在每个个体中正确重复。我可以建议您改用 ggplot2 吗？这可能不是最有效或最优雅的解决方案，但可以让您离您想要的目标更近一步。
我读取了您的数据，并将其命名为 df。
# 如果您尚未安装这些包，请安装它们library(forcats)library(tidyverse)library(reshape2)df$Poblacion <- factor(df$Poblacion)df$ID <- as.numeric(row.names(df))# 为 ggplot 重塑数据集melt.df <- melt(df, id.vars = c("ID","Poblacion"), value.name = "percentage")# 这是为了颠倒因子水平，因为在这里描述的排序 geom_bar 和图例存在问题melt.df$reassigned.origen <- "origen1"melt.df$reassigned.origen[melt.df$variable=="origen1"] <- "origen2"melt.df$ID <- as.numeric(melt.df$ID)melt.df$reassigned.origen <- factor(melt.df$reassigned.origen)# > head(melt.df)# ID Poblacion variable percentage reassigned.origen# 1 1 America origen1 0.006666 origen2# 2 2 America origen1 0.779961 origen2# 3 3 America origen1 0.427611 origen2# 4 4 America origen1 0.813640 origen2# 5 5 America origen1 0.652604 origen2# 6 6 America origen1 0.499865 origen2# 这是为了标记 x 轴；它计算每个地区的中位数 IDID.medians <- aggregate(ID ~ Poblacion, data = melt.df, summary)ggplot(data=melt.df) +# 绘制一个堆叠的柱状图，总和为100%；看起来有点奇怪，但可以得到正确的百分比和水平顺序geom_bar(aes(x=ID, y=percentage, fill = forcats::fct_rev(reassigned.origen),color=Poblacion), stat="identity") +# 这删除了图例的标题theme(legend.title=element_blank()) +# 在 x 轴上添加地区scale_x_continuous(breaks = ID.medians$ID[,3],labels = levels(ID.medians$Poblacion), minor_breaks=NULL) +# x 轴和 y 轴的标签labs(x = "", y = "Percentage origen1")
这是我得到的结果图像：
您可能需要在颜色、因子水平和格式方面做更多的工作。希望这可以帮助您入门。
英文:
Since your Poblacion vector is only of length 5, barplot does not know that you want names.arg to be repeated correctly per each individual. May I suggest that you use ggplot2 instead? This may not be the most efficient or elegant solution but it gets you a few steps closer to what you want.
I read in your data and called it df.
#install these packages if you don't already have them installedlibrary(forcats)library(tidyverse)library(reshape2)df$Poblacion <- factor(df$Poblacion)df$ID <- as.numeric(row.names(df))#reshape the data set for ggplotmelt.df <- melt(df, id.vars = c("ID","Poblacion"), value.name = "percentage")#this is to reverse the factor levels because there is a problem with ordering#geom_bar and legends that is too involved to describe heremelt.df$reassigned.origen<-"origen1"melt.df$reassigned.origen[melt.df$variable=="origen1"]<-"origen2"melt.df$ID <- as.numeric(melt.df$ID)melt.df$reassigned.origen <- factor(melt.df$reassigned.origen)#> head(melt.df)# ID Poblacion variable percentage reassigned.origen#1 1 America origen1 0.006666 origen2#2 2 America origen1 0.779961 origen2#3 3 America origen1 0.427611 origen2#4 4 America origen1 0.813640 origen2#5 5 America origen1 0.652604 origen2#6 6 America origen1 0.499865 origen2#this is for labeling the x axis; it calculates the median ID per regionID.medians <- aggregate(ID ~ Poblacion, data = melt.df, summary)ggplot(data=melt.df) +#plot a stacked bar that sums to 100%; it looks strange but#gets the percentages and levels in the right ordergeom_bar(aes(x=ID, y=percentage, fill = forcats::fct_rev(reassigned.origen),color=Poblacion), stat="identity") +#this removes the title for the legendtheme(legend.title=element_blank()) +#adds the regions at the x axisscale_x_continuous(breaks = ID.medians$ID[,3],labels = levels(ID.medians$Poblacion), minor_breaks=NULL) +#labels for x and y axeslabs(x = "", y = "Percentage origen1")
This is what I get:
You will likely have to do quite a bit more work with colors, factor levels, and formatting. Hopefully this will get you started though.
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