https://github.com/latereshko/Tereshko_neuron_cilia
Tip revision: a975cce55d21d925d6a60157710638e2c54372f4 authored by latereshko on 02 February 2021, 03:35:55 UTC
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Tip revision: a975cce
Figure_S2_v2.R
library(tidyverse)
library(ggpubr)
library(ggbeeswarm)
library(patchwork)
library(dplyr)
library(FSA)
library(lme4)
library(lmerTest)
library(emmeans)
library(kableExtra)
###################
#plotting functions
###################
bees_bars <- function(fillcol) {
list(stat_summary(geom = "bar", fun = mean,
aes(fill = {{ fillcol }}),
width = 0.75, alpha = 1),
geom_quasirandom(aes(colour = {{ fillcol }}),
shape = 16, size=0.8, width = 0.15, alpha = 1),
stat_summary(geom = "errorbar",
fun.data = mean_se, width = 0.5),
scale_y_continuous(expand = c(0,0)),
theme_pubr(),
theme(legend.position = "none",
axis.title.x = element_blank(),
axis.text.x = element_text(size=10, colour="black"),
axis.text.y = element_text(size=10, colour="black"),
axis.ticks = element_line(colour="black",size=0.5))
)
}
###################
###################
###################
###################
###################
#Figure 2C,F exc/inh synapse intensity ()
normint_exc <-read.csv(file.choose(), header=TRUE)
normint_exc48 <-read.csv(file.choose(), header=TRUE)
normint_inh <-read.csv(file.choose(), header=TRUE)
normint_exc_B <- normint_exc %>% filter(Overlay %in% c("GRB_B"))
normint_inh_B <- normint_inh %>% filter(Overlay %in% c("GRB_B"))
normint_exc48_B <- normint_exc48 %>% filter(Overlay %in% c("GRB_B"))
cols1 <- c("CTL" = "grey51","shARL13b_1"= "midnightblue")
dots1 <- c("CTL" = "grey80", "shARL13b_1" = 'blue2',"shARL13b_2" = 'deepskyblue')
cols2 <- c("CTL" = "grey51", "shIFT88_CEP164" = "chartreuse3","shARL13b_2"= "deepskyblue3")
dots2 <- c("CTL" = "grey80", "shIFT88_CEP164" = 'green4',"shARL13b_2" = 'deepskyblue')
p1<-normint_exc_B %>% ggplot(aes(x = Treatment, y = NormAvgTOT)) + bees_bars(fillcol = Treatment) +
scale_fill_manual(values = cols1) + scale_colour_manual(values = dots1) +
ylab("Avg. Total Intensity") + coord_cartesian(ylim = c(0,2.5))
p2<-normint_exc48_B %>% ggplot(aes(x = Treatment, y = NormAvgTOT)) + bees_bars(fillcol = Treatment) +
scale_fill_manual(values = cols2) + scale_colour_manual(values = dots2) +
ylab("Avg. Total Intensity") + coord_cartesian(ylim = c(0,2.5))
p3<-normint_inh_B %>% ggplot(aes(x = Treatment, y = NormAvgTOT)) + bees_bars(fillcol = Treatment) +
scale_fill_manual(values = cols1) + scale_colour_manual(values = dots1) +
ylab("Avg. Total Intensity") + coord_cartesian(ylim = c(0,2.5))
p1+p2+p3
#look at data
ggqqplot(normint_exc_B,"NormAvgTOT",facet.by = "Treatment")
ggdensity(normint_exc_B,"NormAvgTOT",color = "Treatment",palette = cols)
ggqqplot(normint_exc48_B,"NormAvgTOT",facet.by = "Treatment")
ggdensity(normint_exc48_B,"NormAvgTOT",color = "Treatment",palette = cols)
ggqqplot(normint_inh_B,"NormAvgTOT",facet.by = "Treatment")
ggdensity(normint_inh_B,"NormAvgTOT",color = "Treatment",palette = cols)
#linear model 1
lm <- normint_exc_B %>% lmer(data = ., formula = NormAvgTOT~ Treatment + (1 | Dissociation))
lm.emm <- lm %>% emmeans("trt.vs.ctrl" ~ Treatment )
lm.emm$contrasts %>%
rbind(adjust = "dunnett") %>%
kbl() %>% kable_minimal()
plot(lm)
shapiro.test(resid(lm))
qqnorm(resid(lm))
qqline(resid(lm))
#linear model 2
lm <- normint_exc48_B %>% lmer(data = ., formula = log(NormAvgTOT) ~ Treatment + (1 | Dissociation))
lm.emm <- lm %>% emmeans("trt.vs.ctrl" ~ Treatment )
lm.emm$contrasts %>%
rbind(adjust = "dunnett") %>%
kbl() %>% kable_minimal()
plot(lm)
shapiro.test(resid(lm))
qqnorm(resid(lm))
qqline(resid(lm))
#linear model 3
lm <- normint_inh_B %>% lmer(data = ., formula = log(NormAvgTOT) ~ Treatment + (1 | Dissociation))
lm.emm <- lm %>% emmeans("trt.vs.ctrl" ~ Treatment )
lm.emm$contrasts %>%
rbind(adjust = "dunnett") %>%
kbl() %>% kable_minimal()
plot(lm)
shapiro.test(resid(lm))
qqnorm(resid(lm))
qqline(resid(lm))