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.Rhistory
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shiny::runApp('F:/张二爷/开题/shiny_project/Shiny-SoSV-master')
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
image_path <- "F://张二爷//开题//毕业论文//3.nextflow流程研究//2.结果//alpha_acgt_mutation.png"
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
install.packages("magick")
install.packages("png")
runApp()
install.packages("jpeg")
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
runApp()
library(ggplot2)
acgt <- read.csv("F://张二爷//开题//毕业论文//3.nextflow流程研究//2.结果//alpha_acgt.csv")
View(acgt)
sums <- rowSums(acgt)
new_acgt <- data.frame(indicator = indicators, total = sums)
ggplot(new_acgt,aes(x = indicator,y = total))+
geom_bar(stat = "identity")
sums <- rowSums(acgt)
indicators <- c("A_C","A_T","A_G","C_A","C_T","C_G","G_A","G_C","G_T","T_A","T_C","T_G","ALL")
new_acgt <- data.frame(indicator = indicators, total = sums)
ggplot(new_acgt,aes(x = indicator,y = total))+
geom_bar(stat = "identity")
sums <- rowSums(acgt)
indicators <- c("A_C","A_T","A_G","C_A","C_T","C_G","G_A","G_C","G_T","T_A","T_C","T_G","ALL")
new_acgt <- data.frame(indicator = indicators, total = sums)
ggplot(new_acgt,aes(x = indicator,y = total))+
geom_bar(stat = "identity")
acgt <- read.csv("F://张二爷//开题//毕业论文//3.nextflow流程研究//2.结果//alpha_acgt.csv",header = TRUE)
sums <- rowSums(acgt)
indicators <- c("A_C","A_T","A_G","C_A","C_T","C_G","G_A","G_C","G_T","T_A","T_C","T_G","ALL")
new_acgt <- data.frame(indicator = indicators, total = sums)
ggplot(new_acgt,aes(x = indicator,y = total))+
geom_bar(stat = "identity")
View(acgt)
acgt <- read.csv("F://张二爷//开题//毕业论文//3.nextflow流程研究//2.结果//alpha_acgt.csv",row.names = 1)
sums <- rowSums(acgt)
indicators <- c("A_C","A_T","A_G","C_A","C_T","C_G","G_A","G_C","G_T","T_A","T_C","T_G","ALL")
new_acgt <- data.frame(indicator = indicators, total = sums)
ggplot(new_acgt,aes(x = indicator,y = total))+
geom_bar(stat = "identity")
new_acgt
sums
sums <- colSums(acgt)
indicators <- c("A_C","A_T","A_G","C_A","C_T","C_G","G_A","G_C","G_T","T_A","T_C","T_G","ALL")
new_acgt <- data.frame(indicator = indicators, total = sums)
sums
new_acgt
ggplot(new_acgt,aes(x = indicator,y = total))+
geom_bar(stat = "identity")
sums <- colSums(acgt)[1:12]
sums
indicators <- c("A_C","A_T","A_G","C_A","C_T","C_G","G_A","G_C","G_T","T_A","T_C","T_G")
new_acgt <- data.frame(indicators,sums)
ggplot(new_acgt,aes(x = indicators,y = sums))+
geom_point()+
labs(x = "nlucleotide variant",y = "number")
p = ggplot(new_acgt,aes(x = indicators,y = sums))+
geom_point()+
labs(x = "nlucleotide variant",y = "number")
p
library(ggplot2)
ggplot(new_acgt,aes(x = indicators,y = sums))+
geom_point()+
labs(x = "nlucleotide variant",y = "number")
print(ggplot(new_acgt,aes(x = indicators,y = sums))+
geom_point()+
labs(x = "nlucleotide variant",y = "number"))
barplot(sums,names.arg = indicators,col = "skyblue",main = "A, C, G, T 对的和",xlab = "dui",ylab = "he")
ggplot(data, aes(x = indicators, y = sums, fill = indicators)) +
geom_bar(stat = "identity", color = "black") +
labs(title = "A, C, G, T 对的和", x = "对", y = "和") +
theme_minimal()
ggplot(new_acgt, aes(x = indicators, y = sums, fill = indicators)) +
geom_bar(stat = "identity", color = "black") +
labs(title = "A, C, G, T 对的和", x = "对", y = "和") +
theme_minimal()