library(VennDiagram)

data1 <- read.csv("sis_diff_0h-2h.csv", header = TRUE,sep=',',encoding="utf-8",stringsAsFactors=F)
data1=data.frame(data1[,2])
names(data1)<-c("y")
data2 <- read.csv("sis_diff_0h-6h.csv", header = TRUE,sep=',',encoding="utf-8",stringsAsFactors=F)
data2=data.frame(data2[,2])
names(data2)<-c("y")
data3 <- read.csv("sis_diff_0h-12h.csv", header = TRUE,sep=',',encoding="utf-8",stringsAsFactors=F)
data3=data.frame(data3[,2])
names(data3)<-c("y")

venn.plot1 =venn.diagram(
	x = list(data1$y,data2$y,data3$y),
	filename=NULL,
	cex=2.2,
	cat.cex = 2.2,
	fontface = "bold",
	cat.fontface = "bold",
	fontfamily = "Arial",
	cat.fontfamily = "Arial",
	fill=c( "red", "yellow", "blue"),
	margin = 0.05,
	cat.pos = c(-20,20,0),
	cat.dist = c(0.07,0.07,-0.45),
	category = c("0h vs 2h", "0h vs 6h", "0h vs 12h"))

jpeg(file="fig_a.jpg", width=5, height=5, units="in", res=500)
grid.draw(venn.plot1)
dev.off()

library(dplyr)
library(viridis)
library(hrbrthemes)
library(ggplot2)
library(reshape2)
library(forcats)

data <- read.csv("GO_0h_2h.csv", header = TRUE,sep=',',encoding="utf-8")
data=data[order(data$Count),]
p <- data %>%
	ggplot( aes(x=factor(Term, level=Term), y=Count)) +
	geom_bar(stat="identity", fill=c("#37a2da","#fd666d"),width=.4) +
	geom_text(aes(label= Count),vjust=0.5,hjust=-0.3,size=7)+
	coord_flip() +
	ylab("Gene count") +
	xlab("") +
	ylim(0,13)+
	theme_bw()+
	theme(panel.border = element_rect(fill=NA,color="black", size=1, linetype="solid"))+
	theme(plot.margin = unit(c(0.5, 1.5, 0, -0.5), "lines"),
		axis.text.y=element_text(size=20),
		axis.text.x = element_text(size=20),
		axis.title.y=element_text(size=20),
		axis.title.x = element_text(size=20),
		panel.grid.minor.x=element_blank(),
		panel.grid.minor.y=element_blank())

jpeg(file="fig_b.jpg", width=7, height=5, units="in", res=500)
p
dev.off()

library(dplyr)
library(viridis)
library(hrbrthemes)
library(ggplot2)
library(reshape2)
library(forcats)

data <- read.csv("GO_0h_12h.csv", header = TRUE,sep=',',encoding="utf-8")
data=data[order(data$Count),]
p <- data %>%
	ggplot( aes(x=factor(Term, level=Term), y=Count)) +
	geom_bar(stat="identity", fill=c("#5470c6","#91cc75","#fac858","#73c0de","#3ba272","#fc8452","#9a60b4","#ea7ccc","#FF1493","#1E90FF"),width=.8) +
	geom_text(aes(label= Count),vjust=0.5,hjust=-0.3,size=7)+
	coord_flip() +
	ylab("Gene count") +
	xlab("") +
	ylim(0,22)+
	theme_bw()+
	theme(panel.border = element_rect(fill=NA,color="black", size=1, linetype="solid"))+
	theme(plot.margin = unit(c(0.5, 1.5, 0, -0.5), "lines"),
		axis.text.y=element_text(size=20),
		axis.text.x = element_text(size=20),
		axis.title.y=element_text(size=20),
		axis.title.x = element_text(size=20),
		panel.grid.minor.x=element_blank(),
		panel.grid.minor.y=element_blank())

jpeg(file="fig_c.jpg", width=8, height=5, units="in", res=500)
p
dev.off()

library(dplyr)
library(viridis)
library(hrbrthemes)
library(ggplot2)
library(reshape2)
library(TCseq)

raw <- read.csv("clusterData_raw.csv", header = TRUE,sep=',',encoding="utf-8")
a=(raw$intron0_1+raw$intron0_2+raw$intron0_3)/3
b=(raw$intron2_1+raw$intron2_2+raw$intron2_3)/3
c=(raw$intron6_1+raw$intron6_2+raw$intron6_3)/3
d=(raw$intron12_1+raw$intron12_2+raw$intron12_3)/3
raw$a=a
raw$b=b
raw$c=c
raw$d=d
raw=as.matrix(raw)
data=apply(raw[,21:24],2,as.numeric)
rownames(data)=raw[,1]
colnames(data)=c("0hpi","2hpi","6hpi","12hpi")
wssplot <- function(data,nc=15,seed=1234)
{
	wss <- (nrow(data)-1)*sum(apply(data,2,var))
	for (i in 2:nc) {
		set.seed(seed)
		wss[i] <- sum(kmeans(data,centers = i)$withinss)
	}
	plot(1:nc,wss,type = "b",xlab = "Number of Clusters",ylab = "Within groups Sum of Squares")
}
wssplot(data)
set.seed(123)
clust_res <- timeclust(data, algo = 'cm', k = 6, standardize = TRUE)
p <- timeclustplot(clust_res, cols =2,axis.line.size = 0.6, axis.title.size = 24, axis.text.size = 26, title.size = 24, legend.title.size = 24, legend.text.size = 26)

jpeg(file="fig_d_cluster2.jpg", width=8, height=4, units="in", res=500)
p[2]
dev.off()

jpeg(file="fig_d_cluster4.jpg", width=8, height=4, units="in", res=500)
p[4]
dev.off()

jpeg(file="fig_d_cluster5.jpg", width=8, height=4, units="in", res=500)
p[5]
dev.off()