ggplot facet_wrap data.frame的選定列？

我有一個包含點/樣品data.frame X座標X1和X2：ggplot facet_wrap data.frame的選定列？

> head(X) 
           X1  X2 Cluster Timepoint Transcripts  MEF  ESC 
Drop_6_6A_0_TACCTAATCTAC 169.3437 20.18623  2  Day 0  49688 0.4366071 0.3260743 
Drop_6_6A_0_TCAGCTTGTCAC 155.8880 -16.69927  3  Day 0  47365 0.4554254 0.3350818 
Drop_6_6A_0_TCGCAATAAGAT 168.4270 36.50967  2  Day 0  44881 0.4114934 0.2595030 
Drop_6_6A_0_AATCTACCAATC 164.3964 -27.17404  3  Day 0  44640 0.4748225 0.3525822 
Drop_6_6A_0_GGATTAAGTTCA 162.2900 -24.10504  3  Day 0  36822 0.4723676 0.3391785 
Drop_6_6A_0_TGATCTAGTGTC 155.4231 -19.18974  3  Day 0  35889 0.4664174 0.3408899

我想根據相關聯的表達式在散點圖上作爲列添加選擇的標記到X和大小之分值。

NANOG = t(data['NANOG',rownames(X)]) 
SAL4 = t(data['SAL4',rownames(X)]) 
COL5A2 = t(data['COL5A2',rownames(X)]) 
ESRRB = t(data['ESRRB',rownames(X)]) 
ELN = t(data['ELN',rownames(X)]) 
POU5f1 = t(data['POU5F1',rownames(X)]) 
PTN = t(data['PTN',rownames(X)]) 
CXCL5 = t(data['CXCL5',rownames(X)]) 
Z = cbind(X, NANOG, SAL4, POU5f1, ESRRB, COL5A2, ELN, PTN, CXCL5)

結合這些數據後，新data.frame Z看起來是這樣的：

> head(Z) 
           X1  X2 Cluster Timepoint Transcripts  MEF  ESC  NANOG NA POU5F1 ESRRB COL5A2 ELN  PTN  CXCL5 
Drop_6_6A_0_TACCTAATCTAC 169.3437 20.18623  2  Day 0  49688 0.4366071 0.3260743 0.0000000 NA  0  0 5.113106 0 1.004522 0.2645434 
Drop_6_6A_0_TCAGCTTGTCAC 155.8880 -16.69927  3  Day 0  47365 0.4554254 0.3350818 0.2763494 NA  0  0 3.068572 0 1.309109 1.0395819 
Drop_6_6A_0_TCGCAATAAGAT 168.4270 36.50967  2  Day 0  44881 0.4114934 0.2595030 0.0000000 NA  0  0 5.264248 0 0.000000 0.0000000 
Drop_6_6A_0_AATCTACCAATC 164.3964 -27.17404  3  Day 0  44640 0.4748225 0.3525822 0.0000000 NA  0  0 3.554919 0 1.592698 0.2916205 
Drop_6_6A_0_GGATTAAGTTCA 162.2900 -24.10504  3  Day 0  36822 0.4723676 0.3391785 0.0000000 NA  0  0 3.838676 0 1.536569 1.9954283 
Drop_6_6A_0_TGATCTAGTGTC 155.4231 -19.18974  3  Day 0  35889 0.4664174 0.3408899 0.0000000 NA  0  0 4.029014 0 6.187616 0.0000000

現在，我能夠繪製單個散點圖與尺寸相應的表達值的點（如下圖所示），但我不確定如何在一個facet_wrap圖中執行此操作。

library(gridExtra) 
g = arrangeGrob(
    ggplot(Z, aes(X1, X2, color=NANOG)) + ggtitle("NANOG") + 
    geom_point() + 
    xlab(paste0("TSNE1")) + 
    ylab(paste0("TSNE2")) + 
    theme_bw() + theme(axis.line = element_line(colour = "black"), panel.grid.minor = element_blank(), panel.background = element_blank()) + scale_colour_gradient(low='light blue', high='red') + 
    ggsave(paste0(outdir, timepoint, ".tsne.",lab,".density.clustered.all.genes.TSNE1.TSNE2.nanog.expression.no.noise.pdf"), height=pdf_height, width=pdf_width+5), 
    ggplot(Z, aes(X1, X2, color=SAL4)) + ggtitle("SAL4") + 
    geom_point() + 
    xlab(paste0("TSNE1")) + 
    ylab(paste0("TSNE2")) + 
    theme_bw() + theme(axis.line = element_line(colour = "black"), panel.grid.minor = element_blank(), panel.background = element_blank()) + scale_colour_gradient(low='light blue', high='red') + 
    ggsave(paste0(outdir, timepoint, ".tsne.",lab,".density.clustered.all.genes.TSNE1.TSNE2.SAL4.expression.no.noise.pdf"), height=pdf_height, width=pdf_width+5), 
    ggplot(Z, aes(X1, X2, color=POU5f1)) + ggtitle("POU5F1") + 
    geom_point() + 
    xlab(paste0("TSNE1")) + 
    ylab(paste0("TSNE2")) + 
    theme_bw() + theme(axis.line = element_line(colour = "black"), panel.grid.minor = element_blank(), panel.background = element_blank()) + scale_colour_gradient(low='light blue', high='red') + 
    ggsave(paste0(outdir, timepoint, ".tsne.",lab,".density.clustered.all.genes.TSNE1.TSNE2.pou5f1.expression.pdf"), height=pdf_height, width=pdf_width+5), 
    ggplot(Z, aes(X1, X2, color=ESRRB)) + ggtitle("ESRRB") + 
    geom_point() + 
    xlab(paste0("TSNE1")) + 
    ylab(paste0("TSNE2")) + 
    theme_bw() + theme(axis.line = element_line(colour = "black"), panel.grid.minor = element_blank(), panel.background = element_blank()) + scale_colour_gradient(low='light blue', high='red') + 
    ggsave(paste0(outdir, timepoint, ".tsne.",lab,".density.clustered.all.genes.TSNE1.TSNE2.ESRRB.expression.pdf"), height=pdf_height, width=pdf_width+5), 
    ggplot(Z, aes(X1, X2, color=COL5A2)) + ggtitle("COL5A2") + 
    geom_point() + 
    xlab(paste0("TSNE1")) + 
    ylab(paste0("TSNE2")) + 
    theme_bw() + theme(axis.line = element_line(colour = "black"), panel.grid.minor = element_blank(), panel.background = element_blank()) + scale_colour_gradient(low='light blue', high='green') + 
    ggsave(paste0(outdir, timepoint, ".tsne.",lab,".density.clustered.all.genes.TSNE1.TSNE2.col5a2.expression.pdf"), height=pdf_height, width=pdf_width+5), 
    ggplot(Z, aes(X1, X2, color=ELN)) + ggtitle("ELN") + 
    geom_point() + 
    xlab(paste0("TSNE1")) + 
    ylab(paste0("TSNE2")) + 
    theme_bw() + theme(axis.line = element_line(colour = "black"), panel.grid.minor = element_blank(), panel.background = element_blank()) + scale_colour_gradient(low='light blue', high='green') + 
    ggsave(paste0(outdir, timepoint, ".tsne.",lab,".density.clustered.all.genes.TSNE1.TSNE2.eln.expression.pdf"), height=pdf_height, width=pdf_width+5), 
    ggplot(Z, aes(X1, X2, color=PTN)) + ggtitle("PTN") + 
    geom_point() + 
    xlab(paste0("TSNE1")) + 
    ylab(paste0("TSNE2")) + 
    theme_bw() + theme(axis.line = element_line(colour = "black"), panel.grid.minor = element_blank(), panel.background = element_blank()) + scale_colour_gradient(low='light blue', high='green') + 
    ggsave(paste0(outdir, timepoint, ".tsne.",lab,".density.clustered.all.genes.TSNE1.TSNE2.ptn.expression.pdf"), height=pdf_height, width=pdf_width+5), 
    ggplot(Z, aes(X1, X2, color=CXCL5)) + ggtitle("CXCL5") + 
    geom_point() + 
    xlab(paste0("TSNE1")) + 
    ylab(paste0("TSNE2")) + 
    theme_bw() + theme(axis.line = element_line(colour = "black"), panel.grid.minor = element_blank(), panel.background = element_blank()) + scale_colour_gradient(low='light blue', high='green') + 
    ggsave(paste0(outdir, timepoint, ".tsne.",lab,".density.clustered.all.genes.TSNE1.TSNE2.cxcl5.expression.pdf"), height=pdf_height, width=pdf_width+5), 
    nrow=2, ncol=4 
)

上面的代碼工作預期，但很長，而且不足夠大的數，如100，選擇標記..我假設我會以某種方式融Z data.frame？任何幫助將不勝感激。

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2016-09-09 user2117258

請提供可重複的例子。 –

我的博客文章可能會幫助你解決這個問題：https：//drsimonj.svbtle.com/plot-some-variables-against-many-others –

如OP建議的，一種方法是將熔融的原始數據幀Z：

library(reshape2) 
d <- melt(Z, id = 1:5, measure = 6:ncol(Z))

其中id可以是整數（列索引的）或用於ID的變量字符串（列名）的向量，並度量是給出各種度量（本例中爲標記）位置的向量。然後致電ggplot：

library(ggplot2) 
ggplot(d, aes(x = X1, y = X2, size = value)) + 
    geom_point() + 
    facet_wrap(~ variable)

根據需要添加標籤和其他裝飾。使用OP的提取物Z輸出：

來源

2016-09-09 02:44:56

ggplot facet_wrap data.frame的選定列？

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