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将条形图添加到ggplot2图例

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我有以下 data.frame

my.df = data.frame(mean = c(0.045729661,0.030416531,0.043202944,0.025600973,0.040526913,0.046167044,0.029352414,0.021477789,0.027580529,0.017614864,0.020324659,0.027547972,0.0268722,0.030804717,0.021502093,0.008342398,0.02295506,0.022386184,0.030849534,0.017291356,0.030957321,0.01871551,0.016945678,0.014143042,0.026686185,0.020877973,0.028612298,0.013227244,0.010710895,0.024460647,0.03704981,0.019832982,0.031858501,0.022194059,0.030575241,0.024632496,0.040815748,0.025595652,0.023839083,0.026474704,0.033000706,0.044125751,0.02714219,0.025724641,0.020767752,0.026480009,0.016794441,0.00709195), std.dev = c(0.007455271,0.006120299,0.008243454,0.005552582,0.006871527,0.008920899,0.007137174,0.00582671,0.007439398,0.005265133,0.006180637,0.008312494,0.006628951,0.005956211,0.008532386,0.00613411,0.005741645,0.005876588,0.006640122,0.005339993,0.008842722,0.006246828,0.005532832,0.005594483,0.007268493,0.006634795,0.008287031,0.00588119,0.004479003,0.006333063,0.00803285,0.006226441,0.009681048,0.006457784,0.006045368,0.006293256,0.008062195,0.00857954,0.008160441,0.006830088,0.008095485,0.006665062,0.007437581,0.008599525,0.008242957,0.006379928,0.007168385,0.004643819), parent.origin = c("paternal","paternal","paternal","paternal","paternal","paternal","maternal","maternal","maternal","maternal","maternal","maternal","paternal","paternal","paternal","paternal","paternal","paternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","paternal","paternal","paternal","paternal","paternal","paternal","maternal","maternal","maternal","maternal","maternal","maternal","paternal","paternal","paternal","paternal","paternal","paternal"), group = c("F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F"), replicate = c(1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6))

为此我用这段代码生成一个ggplot:

p1 = ggplot(data = my.df, aes(factor(replicate), color = factor(parent.origin)))
p1 = p1 + geom_boxplot(aes(fill = factor(parent.origin),lower = mean - std.dev, upper = mean + std.dev, middle = mean, ymin = mean - 3*std.dev, ymax = mean + 3*std.dev), position = position_dodge(width = 0), width = 0.5, alpha = 0.5, stat="identity") + facet_wrap(~group, ncol = 4)+scale_fill_manual(values = c("red","blue"),labels = c("maternal","paternal"),name = "parental allele")+scale_colour_manual(values = c("red","blue"),labels = c("maternal","paternal"),name = "parental allele")

ggplot

现在我想添加这个data.frame,它给出了以下条形图:

bar.df = data.frame(bar=c("paternal.fraction","maternal.fraction","parental.effect","cross.effect","gender.effect"),vals=c(0.4,0.6,0.82,0.91,0.77))

#order bars and specify colors
bar.df$ord = factor(bar.df$bar,as.character(bar.df$bar))
cols = c(paterna="blue",maternal="red",parental="purple",cross="gray40",gender="gray70")

bar.p = ggplot(bar.df, aes(y=vals))+geom_bar(aes(x=ord),data=bar.df,stat="identity",fill=cols)+labs(x="",y="")

bar chart

位于原始图的传说之下的小图(具有“父母等位基因” Headers 的图片 . )

任何的想法?

2 回答

  • 3

    可能不优雅,但你可以试试这个

    library(grid)
    

    对条形图的最小调整

    bar.p = ggplot(bar.df, aes(y=vals))+
      geom_bar(aes(x=ord),data=bar.df,stat="identity",fill=cols)+
      labs(x="",y="") + theme_bw() +
      theme(axis.text.x = element_text(angle = 90),
            axis.text.y = element_blank(),
            plot.margin=unit(c(0,0,0,0),"mm"))
    
    print(p1)
    subvp = viewport(width = 0.15, height = 0.3, x = 0.9, y = 0.2)
    print(bar.p, vp = subvp)
    

    ggplot with layout

    调整bar.p布局以获得更好的结果 . 这个不是最好的 .

  • 8

    这是grob的做法:

    my.df = data.frame(mean = c(0.045729661,0.030416531,0.043202944,0.025600973,0.040526913,0.046167044,0.029352414,0.021477789,0.027580529,0.017614864,0.020324659,0.027547972,0.0268722,0.030804717,0.021502093,0.008342398,0.02295506,0.022386184,0.030849534,0.017291356,0.030957321,0.01871551,0.016945678,0.014143042,0.026686185,0.020877973,0.028612298,0.013227244,0.010710895,0.024460647,0.03704981,0.019832982,0.031858501,0.022194059,0.030575241,0.024632496,0.040815748,0.025595652,0.023839083,0.026474704,0.033000706,0.044125751,0.02714219,0.025724641,0.020767752,0.026480009,0.016794441,0.00709195), std.dev = c(0.007455271,0.006120299,0.008243454,0.005552582,0.006871527,0.008920899,0.007137174,0.00582671,0.007439398,0.005265133,0.006180637,0.008312494,0.006628951,0.005956211,0.008532386,0.00613411,0.005741645,0.005876588,0.006640122,0.005339993,0.008842722,0.006246828,0.005532832,0.005594483,0.007268493,0.006634795,0.008287031,0.00588119,0.004479003,0.006333063,0.00803285,0.006226441,0.009681048,0.006457784,0.006045368,0.006293256,0.008062195,0.00857954,0.008160441,0.006830088,0.008095485,0.006665062,0.007437581,0.008599525,0.008242957,0.006379928,0.007168385,0.004643819), parent.origin = c("paternal","paternal","paternal","paternal","paternal","paternal","maternal","maternal","maternal","maternal","maternal","maternal","paternal","paternal","paternal","paternal","paternal","paternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","maternal","paternal","paternal","paternal","paternal","paternal","paternal","maternal","maternal","maternal","maternal","maternal","maternal","paternal","paternal","paternal","paternal","paternal","paternal"), group = c("F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:M","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1r:F","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:M","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F","F1i:F"), replicate = c(1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6,1,2,3,4,5,6))
    
    library(ggplot2)
    p1 = ggplot(data = my.df, aes(factor(replicate), color = factor(parent.origin)))
    p1 = p1 + geom_boxplot(aes(fill = factor(parent.origin),lower = mean - std.dev, upper = mean + std.dev, middle = mean, ymin = mean - 3*std.dev, ymax = mean + 3*std.dev), position = position_dodge(width = 0), width = 0.5, alpha = 0.5, stat="identity") + facet_wrap(~group, ncol = 4)+scale_fill_manual(values = c("red","blue"),labels = c("maternal","paternal"),name = "parental allele")+scale_colour_manual(values = c("red","blue"),labels = c("maternal","paternal"),name = "parental allele")
    
    library(grid)
    bar.df = data.frame(bar=c("paternal.fraction","maternal.fraction","parental.effect","cross.effect","gender.effect"),vals=c(0.4,0.6,0.82,0.91,0.77))
    #order bars and specify colors
    bar.df$ord = factor(bar.df$bar,as.character(bar.df$bar))
    #specify bar colors
    cols = c(paterna="blue",maternal="red",parental="purple",cross="gray40",gender="gray70")
    bar.p = ggplot(bar.df, aes(y=vals))+geom_bar(aes(x=ord),data=bar.df,stat="identity",fill=cols)+labs(x="",y="") +theme(axis.text.x = element_text(angle = 90),plot.margin=unit(c(2,2,2,2),"mm"))
    
    library(gridExtra)
    g_legend <- function(a.gplot){
                tmp <- ggplot_gtable(ggplot_build(a.gplot))
                leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
                legend <- tmp$grobs[[leg]]
                return(legend)
        }
    bar.p.grob=ggplotGrob(bar.p)
    p2 = arrangeGrob(p1 + theme(legend.position = "none"),widths=c(3/4, 1/4),arrangeGrob(g_legend(p1),bar.p.grob), ncol = 2)
    

    给出了:
    enter image description here

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