跟着Cancer Cell 学作图| 配对棒棒糖图(Lollipop chart)

news2025/1/10 22:24:03

dotplot

本期图片

❝
Doi：https://doi.org/10.1016/j.ccell.2022.02.013
❞

❝
Dotplot showing the association of cell populations with different tissue types (organ or tumor). The x axis represents cell types, and the y axis represents the different factors defining tissue types. Cell types in the upper panel are associated with the tissue type (tumor/adjacent normal). Green lines represent cells enriched in adjacent tissue, and red lines represent cells enriched in tumors. Cell types in the bottom panel are associated with if the tissue is liver or colon. Orange lines represent cells enriched in the colon, and blue lines represent cells enriched in the liver. Only the cell types with p < 0.05 were highlighted.
❞

复现结果

❝
有些细节上的代码实在懒得调了，大家见谅。可在AI上微调。使用代码时请按需修改，切勿全部套用。
❞

示例数据和代码领取

木舟笔记永久VIP企划

「权益：」

「木舟笔记所有推文示例数据及代码(「在VIP群里」实时更新」）。

data+code
木舟笔记「科研交流群」。

「收费：」

「169￥/人」。可添加微信：mzbj0002 转账（或扫描下方二维码），或直接在文末打赏。

❝
点赞、在看 本文，分享至朋友圈集赞30个并保留30分钟，可优惠20￥。
❞

绘图

data <- read.csv("mmc2.csv")
head(data)
df_order <- data[order(data$Tumor_Pvalue),] 
df_order <- rbind(
  df_order [1:10,],
  df_order[11:48,] %>% arrange(desc(Organ_Pvalue))
)

df_order$tp = ifelse(df_order$Tumor_Pvalue < 0.001, "p < 0.001",
                     ifelse(df_order$Tumor_Pvalue >= 0.001 & df_order$Tumor_Pvalue < 0.01, "0.001< p < 0.01",
                            ifelse(df_order$Tumor_Pvalue >= 0.01 & df_order$Tumor_Pvalue < 0.05, "0.01 < p < 0.05", "p > 0.05")))

df_order$op = ifelse(df_order$Organ_Pvalue < 0.001, "p < 0.001",
                     ifelse(df_order$Organ_Pvalue >= 0.001 & df_order$Organ_Pvalue < 0.01, "0.001< p < 0.01",
                            ifelse(df_order$Organ_Pvalue >= 0.01 & df_order$Organ_Pvalue < 0.05, "0.01 < p < 0.05", "p > 0.05")))
df_order$tp <-factor(df_order$tp,levels = c("p > 0.05","0.01 < p < 0.05","0.001< p < 0.01","p < 0.001"))
df_order$op <- factor(df_order$op,levels = c("p > 0.05","0.01 < p < 0.05","0.001< p < 0.01","p < 0.001"))
df_order$Enriched <- factor(df_order$Enriched, levels = c('Tumor','Adjacent','Liver','Colon') )
df_order$Celltype <- factor(df_order$Celltype, levels = df_order$Celltype)
head(df_order)
## plot
ggplot(df_order)+
  geom_segment(aes(x = Celltype,xend = Celltype,
                   y = 0,yend = -log10(Tumor_Pvalue),
                   color = Enriched_T),size = 0.7) +
  geom_segment(aes(x = Celltype,xend = Celltype,
                   y = 0,yend = log10(Organ_Pvalue),
                   color = Enriched_O),size = 0.7) +
  scale_color_manual(values = c('#d8ddde','#3f9c49','#ed301a','#faa25c','#3fabd6'))+
  geom_point(
    aes(x=Celltype, y=-log10(Tumor_Pvalue),fill = tp),
    size = 4,shape = 21,color = 'white'
  ) +
  scale_fill_manual(values = c('#d8ddde','#f1bbc0','#db5e64','#b12c20')) +
  geom_point(
    aes(x=Celltype, y=log10(Organ_Pvalue),fill = op),
    size = 4,shape = 21,color = 'white'
  ) +
  geom_hline(yintercept = 0, linetype = "dashed",size = 1) +
  theme_classic()+
  xlab('')+
  theme(axis.text.x = element_text(angle = 45, hjust = 1,size = 8))

ggsave('dotplot.pdf',width = 8,height = 6)