R ggplot2：如何自定义点的颜色和形状？

我正在尝试使用

ggplot2

创建条形图。下面是

tbl

的子集，其中包含我正在使用的相关列，以及

dput

> tbl[,c('Study_ID', 'Probe_ID', 'Group1','Group2','LogFC', 'adj_P_Value', 'P_Value', 'CI_L','CI_R','Disease')]
   Study_ID  Probe_ID               Group1                   Group2       LogFC  adj_P_Value      P_Value        CI_L        CI_R
1   GSE2461 220307_at                 Male                   Female -0.09017596 1.000000e+00 5.662047e-01 -0.43955752  0.25920561
2   GSE2461 220307_at   ulcerative colitis irritable bowel syndrome  0.08704844 1.000000e+00 5.784053e-01 -0.26134341  0.43544028
3  GSE27887 220307_at     nonlesional skin            lesional skin -0.03501474 1.000000e+00 4.409881e-01 -0.12677636  0.05674688
4  GSE27887 220307_at         pretreatment            posttreatment  0.01096914 1.000000e+00 8.080366e-01 -0.08064105  0.10257932
5  GSE42296   7921677           Infliximab         Before treatment -0.03707265 1.000000e+00 3.979403e-01 -0.12407201  0.04992672
6  GSE42296   7921677            Responder             Nonresponder  0.07644834 1.000000e+00 1.505444e-01 -0.02849309  0.18138977
7  GSE42296   7921677 Rheumatoid Arthritis          Crohn's Disease  0.42318863 3.960125e-06 1.989713e-10  0.31076269  0.53561457
8  GSE58558 220307_at                    M                        F -0.11881801 1.000000e+00 1.130180e-01 -0.26629675  0.02866072
9  GSE58558 220307_at    non lesional skin            lesional skin -0.18914128 1.000000e+00 3.696739e-03 -0.31525660 -0.06302596
10 GSE58558 220307_at            responder             nonresponder -0.14470319 1.000000e+00 2.328062e-01 -0.38396386  0.09455748
11 GSE58558 220307_at              week 12                    day 1 -0.39619004 4.311942e-01 2.215798e-05 -0.57226227 -0.22011781
12 GSE58558 220307_at               week 2                    day 1 -0.28765455 1.000000e+00 8.753977e-04 -0.45375957 -0.12154953
13 GSE59294 220307_at   C Dupilumab 300 mg       B Dupilumab 150 mg  0.16853309 1.000000e+00 1.140155e-01 -0.04273877  0.37980494
14 GSE59294 220307_at            D Placebo       B Dupilumab 150 mg -0.18995566 1.000000e+00 2.264691e-01 -0.50367856  0.12376724
15 GSE59294 220307_at              NL skin                  LS skin  0.01376129 1.000000e+00 9.041383e-01 -0.21711706  0.24463964
16 GSE59294 220307_at                  Pre                     Post  0.02234607 1.000000e+00 8.069367e-01 -0.16235054  0.20704268
                                        Disease
1  irritable bowel syndrome; ulcerative colitis
2  irritable bowel syndrome; ulcerative colitis
3                             atopic Dermatitis
4                             atopic Dermatitis
5         Crohn's Disease; Rheumatoid Arthritis
6         Crohn's Disease; Rheumatoid Arthritis
7         Crohn's Disease; Rheumatoid Arthritis
8                             Atopic Dermatitis
9                             Atopic Dermatitis
10                            Atopic Dermatitis
11                            Atopic Dermatitis
12                            Atopic Dermatitis
13                            atopic Dermatitis
14                            atopic Dermatitis
15                            atopic Dermatitis
16                            atopic Dermatitis

以下是

dput

：

> dput(droplevels(tbl[,c('Study_ID', 'Probe_ID', 'Group1','Group2','LogFC', 'adj_P_Value', 'P_Value', 'CI_L','CI_R','Disease')]))
structure(list(Study_ID = c("GSE2461", "GSE2461", "GSE27887", 
"GSE27887", "GSE42296", "GSE42296", "GSE42296", "GSE58558", "GSE58558", 
"GSE58558", "GSE58558", "GSE58558", "GSE59294", "GSE59294", "GSE59294", 
"GSE59294"), Probe_ID = c("220307_at", "220307_at", "220307_at", 
"220307_at", "7921677", "7921677", "7921677", "220307_at", "220307_at", 
"220307_at", "220307_at", "220307_at", "220307_at", "220307_at", 
"220307_at", "220307_at"), Group1 = c("Male", "ulcerative colitis", 
"nonlesional skin", "pretreatment", "Infliximab", "Responder", 
"Rheumatoid Arthritis", "M", "non lesional skin", "responder", 
"week 12", "week 2", "C Dupilumab 300 mg", "D Placebo", "NL skin", 
"Pre"), Group2 = c("Female", "irritable bowel syndrome", "lesional skin", 
"posttreatment", "Before treatment", "Nonresponder", "Crohn's Disease", 
"F", "lesional skin", "nonresponder", "day 1", "day 1", "B Dupilumab 150 mg", 
"B Dupilumab 150 mg", "LS skin", "Post"), LogFC = c(-0.0901759558643281, 
0.0870484364429408, -0.0350147376937934, 0.0109691380052655, 
-0.0370726462749328, 0.0764483363743359, 0.423188628619509, -0.118818013184408, 
-0.189141277685995, -0.144703191279992, -0.396190039768736, -0.28765454670704, 
0.168533085440721, -0.189955660434197, 0.0137612879743023, 0.0223460675171673
), adj_P_Value = c(1, 1, 1, 1, 1, 1, 3.96012504622782e-06, 1, 
1, 1, 0.431194244819507, 1, 1, 1, 1, 1), P_Value = c(0.566204678925109, 
0.578405275354266, 0.440988072013756, 0.808036622723435, 0.397940346528484, 
0.150544373610059, 1.98971262936634e-10, 0.11301796668591, 0.00369673863311212, 
0.232806229179741, 2.21579776371792e-05, 0.000875397680320129, 
0.114015475901252, 0.226469133014055, 0.904138332714553, 0.806936684043586
), CI_L = c(-0.439557521861354, -0.261343410788222, -0.12677635951562, 
-0.0806410486876688, -0.124072011981945, -0.0284930943795223, 
0.310762687356251, -0.26629674914578, -0.315256597358499, -0.383963864121397, 
-0.57226227039893, -0.453759565458485, -0.0427387734415052, -0.503678563834605, 
-0.217117064412363, -0.162350541147386), CI_R = c(0.259205610132698, 
0.435440283674103, 0.0567468841280329, 0.1025793246982, 0.0499267194320791, 
0.181389767128194, 0.535614569882768, 0.0286607227769647, -0.0630259580134921, 
0.0945574815614131, -0.220117809138542, -0.121549527955595, 0.379804944322947, 
0.12376724296621, 0.244639640360967, 0.207042676181721), Disease = c("irritable bowel syndrome; ulcerative colitis", 
"irritable bowel syndrome; ulcerative colitis", "atopic Dermatitis", 
"atopic Dermatitis", "Crohn's Disease; Rheumatoid Arthritis", 
"Crohn's Disease; Rheumatoid Arthritis", "Crohn's Disease; Rheumatoid Arthritis", 
"Atopic Dermatitis", "Atopic Dermatitis", "Atopic Dermatitis", 
"Atopic Dermatitis", "Atopic Dermatitis", "atopic Dermatitis", 
"atopic Dermatitis", "atopic Dermatitis", "atopic Dermatitis"
)), .Names = c("Study_ID", "Probe_ID", "Group1", "Group2", "LogFC", 
"adj_P_Value", "P_Value", "CI_L", "CI_R", "Disease"), row.names = c(NA, 
-16L), class = "data.frame")

最后，这里是我到目前为止的代码

#test using ggplot2
maxFC = max(as.numeric(as.character(tbl$LogFC)))
minFC = min(as.numeric(as.character(tbl$LogFC)))


datasetList = tbl$Study_ID
hLines =(which(duplicated(datasetList) == FALSE) - 0.5)


tbl$ylab <- paste(tbl$Group2," \U2192 ","\n", tbl$Group1, sep = "")


p <- ggplot(data = tbl, aes(x = LogFC, y = Probe_ID, group = Study_ID)) +
  geom_vline(xintercept = log(0.5,2), size = 0.2) +
  geom_vline(xintercept = log(2/3,2), size = 0.2) +
  geom_vline(xintercept = log(1.5,2), size = 0.2) +
  geom_vline(xintercept = log(2,2), size = 0.2) +
  labs(title = tbl$gene, y = "Contrasts", x = bquote(~Log[2]~'(Fold Change)')) +
  geom_errorbarh(aes(x = LogFC, xmin =  CI_L, xmax = CI_R), height = .1) +
  geom_point(aes(colour = cut(adj_P_Value, c(-Inf, 0.01, 0.05, Inf)))) +
  scale_color_manual(name = "P Value",
                     values = c("(-Inf,0.01]" = "red",
                                "(0.01,0.05)" = "orange",
                                "(0.05, Inf]" = "black"),
                     labels = c("<= 0.01", "0.01 < P Value <= 0.05", "> 0.05")) +
  scale_shape_manual(values = c( 4,15,19)) +
  coord_cartesian(xlim = c(min(-2,minFC),max(2,maxFC))) +

  theme(axis.text.y = element_blank(), strip.text.y = element_text(angle = 180),
        #panel.grid.major = element_blank(),
        #panel.grid.minor = element_blank(),
        axis.line.y = element_blank(),
        axis.line.x = element_blank(),
        #panel.background = element_rect(fill = 'white', colour = 'white'),
        #panel.grid = element_blank(),
        panel.spacing.y = unit(0.5,'lines'),
        axis.ticks.y = element_blank()) +
  facet_grid(Study_ID+ylab~ ., scales = 'free', space = 'free', switch = 'both')


p

---

添加所需系数的列

library(dplyr)
tbl <- tbl %>% 
         mutate(colourgroup = case_when(
                                   adj_P_Value <= 0.01 ~ 1,
                                   adj_P_Value > 0.01 & adj_P_Value < 0.05 ~ 2,
                                   adj_P_Value >= 0.05 ~ 3 ))

到

及

最小示例 这个最小的

ggplot

命令对我有效。注：我故意切换了

x

和

y

值，而

红色

和

橙色

可能很难区分

ggplot(df2, aes(x = Probe_ID, y=LogFC, colour=factor(colourgroup), shape=factor(colourgroup))) +
  geom_point() +
  scale_color_manual(values=c("red","orange","black")) +
  scale_shape_manual(values=c(1,2,3))

---

然后我可以自由地删除

geom\u点

和两条

scale\u*

线，对吗？还有，

TRUE~as.character（x）

在做什么？在

TRUE~as.factor（x）

上出现错误，说“未找到对象‘x’”，请参见我的编辑。。在

ggplot（）

中的某个点上，我得到了一个错误“提供给离散刻度的连续值”，这个错误很奇怪，仍然给了我相同的错误。您的代码与我在SabeE**函数中除了<代码> Value= C（..）<代码>之外的更新一样，如果下面的答案是有用的，请考虑通过点击左边的检查标记来接受它。这让社区知道问题已经解决。如果没有帮助，不用担心

aes(x = LogFC, y = Probe_ID, group = Study_ID) 

aes(x = LogFC, y = Probe_ID, colour = factor(colourgroup), shape = factor(colourgroup))

scale_color_manual(values=c("red","orange","black")) +
scale_shape_manual(values=c(1,2,3))

ggplot(df2, aes(x = Probe_ID, y=LogFC, colour=factor(colourgroup), shape=factor(colourgroup))) +
  geom_point() +
  scale_color_manual(values=c("red","orange","black")) +
  scale_shape_manual(values=c(1,2,3))