R中的火山图：添加细节：仅为公共因子着色

我有一个问题，就是在两个数据集中（整个冒号/火山）给一些基因着色以指定常见基因。 下面的代码运行良好。然而，问题是，我想补充一些细节，这是相当棘手的

我想为普通基因应用不同的颜色（红色会更好）：只有在满足以下条件的情况下：（整结肠$genes==火山$genes）。 我试图将组划分为（指定的增加/指定的减少）但遗憾的是没有成功

这是我的代码附件

非常感谢

    #volcano plot using ggplot2
    library(data.table)
    # Adding group to decipher if the gene is significant or not:
    whole_colon <- data.frame(whole_colon)
    whole_colon["group"] <- "NotSignificant"
    whole_colon[which(whole_colon['FDR'] < 0.05 & whole_colon['logFC'] > 1.5),"group"] <- "Increased"
    whole_colon[which(volcano['FDR'] < 0.05 & volcano['logFC'] > 1.5),"group"] <- "colon_Increased_specialized"
    whole_colon[which(volcano['FDR'] < 0.05 & volcano['logFC'] < -1.5),"group"] <- "colon_Decreased_specialized"

    with(subset(whole_colon , FDR<0.05), points(logFC, -log10(FDR), pch=20,col="red"), whole_colon$genes==volcano$genes)

    library(ggplot2)
    ggplot(whole_colon, aes(x = logFC, y = -log10(FDR), color = group))+
      scale_colour_manual(values = cols) +
      ggtitle(label = "Volcano Plot", subtitle = "colon specific volcano plot") +
      geom_point(size = 2.5, alpha = 1, na.rm = T) +
      theme_bw(base_size = 14) + 
      theme(legend.position = "right") + 
      xlab(expression(log[2]("logFC"))) + 
      ylab(expression(-log[10]("FDR"))) +
      geom_hline(yintercept = 1.30102, colour="#990000", linetype="dashed") + 
      geom_vline(xintercept = 1.5849, colour="#990000", linetype="dashed") + 
      geom_vline(xintercept = -1.5849, colour="#990000", linetype="dashed")+ 
      scale_y_continuous(trans = "log1p")

火山：

     genes   logFC       FDR             group    
1   INHBA   6.271879    2.070000e-30    Increased
2   COL10A1 7.634386    1.820000e-23    Increased
3   WNT2    9.485133    6.470000e-20    Increased
4   COL8A1  3.974965    6.470000e-20    Increased
5   THBS2   4.104176    2.510000e-19    Increased
6   BGN     3.524484    5.930000e-18    Increased
7   COMP    11.916956   2.740000e-17    Increased
9   SULF1   3.540374    1.290000e-15    Increased
10  CTHRC1  3.937028    4.620000e-14    Increased
11  TRIM29  3.827088    1.460000e-11    Increased
12  SLC6A20 5.060538    5.820000e-11    Increased
13  SFRP4   5.924330    8.010000e-11    Increased
14  CDH3    5.330732    8.940000e-11    Increased
15  ESM1    6.491496    3.380000e-10    Increased
614 TDP2    -1.801368   0.002722461     NotSignificant
615 EPHX2   -1.721039   0.002722461     NotSignificant
616 RAVER2  -1.581812   0.002749728     NotSignificant
617 BMP6    -2.702780   0.002775460     Increased
619 SCNN1G  -4.012111   0.002870500     Increased
620 SLC52A3 -1.868920   0.002931197     NotSignificant
621 VIPR1   -1.556238   0.002945578     NotSignificant
622 SUCLG2  -1.720993   0.003059717     NotSignificant

---

提供的示例数据集不完整，因为没有重叠，因此很难根据该数据集进行颜色编码。请尝试以下操作，关键是您不能使用

==

，而是要使用%中的

%返回一个布尔值，以确定
整号
中的基因是否位于
火山
：

whole_colon=structure(list(genes = structure(c(5L, 11L, 3L, 
7L, 10L, 1L, 
2L, 9L, 6L, 8L, 12L, 4L, 13L, 14L), .Label = c("BEST4", "COL10A1", 
"COL11A1", "COL8A1", "CST1", "GUCA2B", "INHBA", "KRT6B", "MMP11", 
"MMP7", "OTOP2", "WNT2", "ABC", "DEF"), class = "factor"), logFC = c(9.554742, 
-9.408177, 6.825363, 6.271879, 7.594926, -7.756451, 7.634386, 
4.767644, -6.346156, 11.80155, 9.485133, 3.974965, 0.5, -0.5), 
    FDR = c(5.64e-45, 5.76e-32, 1e-31, 2.07e-30, 2.07e-30, 8.3e-30, 
    1.82e-23, 2.7e-23, 2.17e-21, 5.37e-20, 6.47e-20, 6.47e-20, 
    1, 1), group = c("Increased", "Decreased", "Increased", "specific_Increased", 
    "Increased", "Decreased", "specific_Increased", "Increased", 
    "Decreased", "Increased", "specific_Increased", "specific_Increased", 
    "NotSignificant", "NotSignificant")), row.names = c("1", 
"3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", 
"2"), class = "data.frame")

设置组：

#set the decreased and increased like you did:
whole_colon["group"] <- "NotSignificant"
whole_colon[which(whole_colon['FDR'] < 0.05 & whole_colon['logFC'] > 1.5),"group"] <- "Increased"
whole_colon[which(whole_colon['FDR'] < 0.05 & -whole_colon['logFC'] > 1.5),"group"] <- "Decreased"
whole_colon[which(whole_colon['FDR'] < 0.05 & whole_colon['logFC'] > 1.5 & whole_colon$genes %in% volcano$genes),"group"] <- "specific_Increased"
whole_colon[which(whole_colon['FDR'] < 0.05 & whole_colon['logFC'] < -1.5 & whole_colon$genes %in% volcano$genes),"group"] <- "specific_Decreased"

#
提供的示例数据集不完整，因为没有重叠，因此很难根据该数据集进行颜色编码。请尝试以下操作，关键是您不能使用
==
，而是要使用%
中的
%返回一个布尔值，以确定
整号
中的基因是否位于
火山
：

whole_colon=structure(list(genes = structure(c(5L, 11L, 3L, 
7L, 10L, 1L, 
2L, 9L, 6L, 8L, 12L, 4L, 13L, 14L), .Label = c("BEST4", "COL10A1", 
"COL11A1", "COL8A1", "CST1", "GUCA2B", "INHBA", "KRT6B", "MMP11", 
"MMP7", "OTOP2", "WNT2", "ABC", "DEF"), class = "factor"), logFC = c(9.554742, 
-9.408177, 6.825363, 6.271879, 7.594926, -7.756451, 7.634386, 
4.767644, -6.346156, 11.80155, 9.485133, 3.974965, 0.5, -0.5), 
    FDR = c(5.64e-45, 5.76e-32, 1e-31, 2.07e-30, 2.07e-30, 8.3e-30, 
    1.82e-23, 2.7e-23, 2.17e-21, 5.37e-20, 6.47e-20, 6.47e-20, 
    1, 1), group = c("Increased", "Decreased", "Increased", "specific_Increased", 
    "Increased", "Decreased", "specific_Increased", "Increased", 
    "Decreased", "Increased", "specific_Increased", "specific_Increased", 
    "NotSignificant", "NotSignificant")), row.names = c("1", 
"3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", 
"2"), class = "data.frame")

设置组：

#set the decreased and increased like you did:
whole_colon["group"] <- "NotSignificant"
whole_colon[which(whole_colon['FDR'] < 0.05 & whole_colon['logFC'] > 1.5),"group"] <- "Increased"
whole_colon[which(whole_colon['FDR'] < 0.05 & -whole_colon['logFC'] > 1.5),"group"] <- "Decreased"
whole_colon[which(whole_colon['FDR'] < 0.05 & whole_colon['logFC'] > 1.5 & whole_colon$genes %in% volcano$genes),"group"] <- "specific_Increased"
whole_colon[which(whole_colon['FDR'] < 0.05 & whole_colon['logFC'] < -1.5 & whole_colon$genes %in% volcano$genes),"group"] <- "specific_Decreased"

#
我想我解决了这个问题。只要再加上一句话，这个问题就解决了。
在调整了@StupidWolf的建议和对col的lil重新定义过程后，我得到了我想要的图像

cols<- c(red="red", orange="orange", NotSignificant="darkgrey", Increased= "#00B2FF" ,Decreased="#00B2FF", specific_Increased="#ff4d00", specific_Decreased="#ff4d00" )
head(cols)

cols我想我解决了这个问题。只要再加上一句话，这个问题就解决了。
在调整了@StupidWolf的建议和对col的lil重新定义过程后，我得到了我想要的图像

cols<- c(red="red", orange="orange", NotSignificant="darkgrey", Increased= "#00B2FF" ,Decreased="#00B2FF", specific_Increased="#ff4d00", specific_Decreased="#ff4d00" )
head(cols)

coli我怀疑这是否能帮助你解决问题，但是，他们确实有一个名为“COL8A1”的公共数据（如果你愿意，我可以更改此样本数据以包含更多的公共基因）。为了说明这一点，我只寻找一个相同的冒号[基因]，而不是整个数据行。不幸的是，这个命令也没有起作用。给了我一张“整号”数据的完整图像[这是进度！！]但仍然缺少涉及通用数据集的颜色标记。您想对另一个数据集中的重要组和发现的组进行颜色编码，对吗？即5个不同组，重要上/下，不重要，重要上/下，在火山中发现，我是否正确获得了这一点？您需要为您的数据集的向量colsThanks指定5种颜色因为有帮助，是的，我很想给它们涂上不同的颜色，但不是所有这5个扇区都需要不同的颜色。上面的颜色已经足够了，而我们只需再加上一个“红色”加上“增加的比色”和“减少的比色”，我怀疑这是否能帮你解决问题，但是，它们确实有共同的数据称为“COL8A1”（如果您愿意，我可以更改此示例数据以包含更多常见的基因）。为了澄清这一点，我只希望一个冒号[基因]是相同的，而不是整个数据行。而且这个命令也没有起作用。给了我一个完整的“整冒号”数据图像[这是一个进步！！]但仍然缺少涉及通用数据集的颜色标记。您想对另一个数据集中的重要组和发现的组进行颜色编码，对吗？即5个不同组，重要上/下，不重要，重要上/下，在火山中发现，我是否正确获得了这一点？您需要为您的数据集的向量colsThanks指定5种颜色由于您的帮助，是的，我很想用不同的颜色，但并非所有这5个扇区都需要不同的颜色。上面的颜色已经足够了，而我们只需再添加一个“红色”和“特定颜色增加”和“特定颜色减少”