library(lme4) library(ggplot2) library(agricolae) library(ggpubr) library(car) library(forcats) data = read.table("D:/ryby/AndroallR.csv", header = T, sep = ";") data$Individual <- factor(data$Individual, labels = c("AN", "karl", "kontrola")) AN <- data[which(data$Individual == "AN"), names(data)] shapiro.test(AN$Fluorescence_x10) karl <- data[which(data$Individual == "karl"), names(data)] shapiro.test(karl$Fluorescence_x10) kontrola <- data[which(data$Individual == "kontrola"), names(data)] shapiro.test(kontrola$Fluorescence_x10) ####box#### data$Type <- factor(data$Type, levels = c("Normal androgenetic", "Dwarf androgenetic", "Control", "L5178Y-R")) ggplot(data, aes(x = data$Type, y = data$Fluorescence_x10)) + geom_boxplot(stat = 'boxplot', colour= 'black', fill = 'deepskyblue2')+ ylab('Telomere length-related fluorescence (TLF)')+ xlab('')+ theme(axis.title.x = element_text(face="bold"), axis.title.y = element_text(face="bold")) ####regresja#### ggplot(data, aes(x=Length, y=Fluorescence_x10 )) + geom_point(shape=2) + scale_colour_hue(l=50) + # Use a slightly darker palette than normal geom_smooth(method=lm, # Add linear regression lines se=FALSE, #Confidance region fullrange=TRUE)+ xlab("Length [cm]")+ ylab("Intensity x10") ggplot(data, aes(x=Weigth, y=Fluorescence_x10 )) + geom_point(shape=16) + scale_colour_hue(l=50) + # Use a slightly darker palette than normal geom_smooth(method=lm, # Add linear regression lines se=FALSE, #Confidance region fullrange=TRUE)+ xlab("Weigth [g]")+ ylab("Intensity x10") ggplot(AN, aes(x=Length, y=Fluorescence_x10 )) + geom_point(shape=2) + scale_colour_hue(l=50) + # Use a slightly darker palette than normal geom_smooth(method=lm, # Add linear regression lines se=FALSE, #Confidance region fullrange=TRUE)+ xlab("Length [cm]")+ ylab("Telomere length-related fluorescence (TLF) ") ggplot(AN, aes(x=Weigth, y=Fluorescence_x10 )) + geom_point(shape=16) + scale_colour_hue(l=50) + # Use a slightly darker palette than normal geom_smooth(method=lm, # Add linear regression lines se=FALSE, #Confidance region fullrange=TRUE)+ xlab("Weigth [g]")+ ylab("Telomere length-related fluorescence (TLF) ") ggplot(karl, aes(x=Length, y=Fluorescence_x10 )) + geom_point(shape=2) + scale_colour_hue(l=50) + # Use a slightly darker palette than normal geom_smooth(method=lm, # Add linear regression lines se=FALSE, #Confidance region fullrange=TRUE)+ xlab("Length [cm]")+ ylab("Telomere length-related fluorescence (TLF) ") ggplot(karl, aes(x=Weigth, y=Fluorescence_x10 )) + geom_point(shape=16) + scale_colour_hue(l=50) + # Use a slightly darker palette than normal geom_smooth(method=lm, # Add linear regression lines se=FALSE, #Confidance region fullrange=TRUE)+ xlab("Weigth [g]")+ ylab("Telomere length-related fluorescence (TLF) ") ggplot(kontrola, aes(x=Length, y=Fluorescence_x10 )) + geom_point(shape=2) + scale_colour_hue(l=50) + # Use a slightly darker palette than normal geom_smooth(method=lm, # Add linear regression lines se=FALSE, #Confidance region fullrange=TRUE)+ xlab("Length [cm]")+ ylab("Telomere length-related fluorescence (TLF) ") ggplot(kontrola, aes(x=Weigth, y=Fluorescence_x10 )) + geom_point(shape=16) + scale_colour_hue(l=50) + # Use a slightly darker palette than normal geom_smooth(method=lm, # Add linear regression lines se=FALSE, #Confidance region fullrange=TRUE)+ xlab("Weigth [g]")+ ylab("Telomere length-related fluorescence (TLF) ") cor.test(data$Fluorescence_x10, data$Length) cor.test(data$Fluorescence_x10, data$Weigth) cor.test(AN$Fluorescence_x10, AN$Length) cor.test(AN$Fluorescence_x10, AN$Weigth) cor.test(karl$Fluorescence_10x, karl$Length) cor.test(karl$Fluorescence_10x, karl$Weigth) cor.test(kontrola$Fluorescence_x10, kontrola$Length) cor.test(kontrola$Fluorescence_x10, kontrola$Weigth) ####ANOVA fluorescence#### andro_dwarf = data[which(data$Type == "Dwarf"|data$Type == "Androgenetic" ), names(data)] Anova_andro_dwarf <- aov(andro_dwarf$Fluorescence_x10 ~ andro_dwarf$Type) summary(Anova_andro_dwarf) andro_control = data[which(data$Type == "Androgenetic"|data$Type == "Control" ), names(data)] Anova_andro_control <- aov(andro_control$Fluorescence_x10 ~ andro_control$Type) summary(Anova_andro_control) dwarf_control = data[which(data$Type == "Dwarf"|data$Type == "Control" ), names(data)] Anova_dwarf_control <- aov(dwarf_control$Fluorescence_x10 ~ dwarf_control$Type) summary(Anova_dwarf_control) ####ANOVA waga i wzrost#### andro_dwarf = data[which(data$Type == "Dwarf"|data$Type == "Androgenetic" ), names(data)] Anova_andro_dwarf <- aov(andro_dwarf$Length ~ andro_dwarf$Type) summary(Anova_andro_dwarf) andro_control = data[which(data$Type == "Androgenetic"|data$Type == "Control" ), names(data)] Anova_andro_control <- aov(andro_control$Length ~ andro_control$Type) summary(Anova_andro_control) dwarf_control = data[which(data$Type == "Dwarf"|data$Type == "Control" ), names(data)] Anova_dwarf_control <- aov(dwarf_control$Length ~ dwarf_control$Type) summary(Anova_dwarf_control) andro_dwarf = data[which(data$Type == "Dwarf"|data$Type == "Androgenetic" ), names(data)] Anova_andro_dwarf <- aov(andro_dwarf$Weigth ~ andro_dwarf$Type) summary(Anova_andro_dwarf) andro_control = data[which(data$Type == "Androgenetic"|data$Type == "Control" ), names(data)] Anova_andro_control <- aov(andro_control$Weigth ~ andro_control$Type) summary(Anova_andro_control) dwarf_control = data[which(data$Type == "Dwarf"|data$Type == "Control" ), names(data)] Anova_dwarf_control <- aov(dwarf_control$Weigth ~ dwarf_control$Type) summary(Anova_dwarf_control) ####hw#### leveneTest(andro_dwarf$Length, andro_dwarf$Type) leveneTest(andro_dwarf$Fluorescence_x10, andro_dwarf$Type) leveneTest(andro_dwarf$Weigth, andro_dwarf$Type) leveneTest(andro_control$Length, andro_control$Type) leveneTest(andro_control$Fluorescence_x10, andro_control$Type) leveneTest(andro_control$Weigth, andro_control$Type) leveneTest(dwarf_control$Length, dwarf_control$Type) leveneTest(dwarf_control$Fluorescence_x10, dwarf_control$Type) leveneTest(dwarf_control$Weigth, dwarf_control$Type) kruskal.test(dwarf_control$Weigth~dwarf_control$Type)