1. KEGG bubble plot


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setwd("C:/Users/hope/Desktop/Bio-scripts/R")
library(tidyverse)
library(ggplot2)

data = read.csv("LXY.csv",quote="",header = T)
head(data)
########
KEGG PATHWAY	Total	Hits	Rich factor	P-value	Impact
Aminoacyl-tRNA biosynthesis	67	11	0.164179104	5.34E-05	0.09302
Flavonoid biosynthesis	43	6	0.139534884	0.0075289	0.21899
Ascorbate and aldarate metabolism	15	3	0.2	0.022171	0
Glyoxylate and dicarboxylate metabolism	17	3	0.176470588	0.031228	0.40476
########
kegg = data[,c(1,3,4,5)]
kg = transmute(kegg,KEGG.PATHWAY,Hits,Rich_factor=Rich.factor,P.value)

mid <- mean(kg$P.value)

ggplot(kg,aes(x = Rich_factor, y = KEGG.PATHWAY, size = Hits)) + 
  geom_point(aes(col=P.value),alpha=0.8) +
  ggtitle("Statistics of Pathway Enrichment") +
  labs(x = "Rich factor", y = "",size = "metabolism\n   number", col = "p-value") +
  scale_colour_gradient2(midpoint = mid, low = "red", mid = "green",
                          high = "purple")+
  scale_size(range = c(2,10)) +
  theme_bw() +
  theme()
ggsave("KEGG.svg", width = 10, height = 8)

2. Genome_Scripts: A repository for scripts used in genome project

3. Figure for genome of black pepper

4. 截断bar图

5. 差异基因火山图

6. 拟时序热图

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