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Protocol for determining the average speed and frequency of kinesin and dynein driven Intraflagellar Transport (IFT) in C. elegans

This repository contains R codes used for generating the IFT frequency graph and stats (given below) published from "Protocol for determining the average speed and frequency of kinesin and dynein driven Intraflagellar Transport (IFT) in C. elegans." paper.

Rplot

doi: TIF movies used for generaring the freqency graph are found at Zenodo, https://doi.org/10.5281/zenodo.6568214 .

Steps for generating boxplot from .csv file.

1. Upload required packages and read .csv file.

library(ggpubr)
library(dplyr)
library(tidyr)
library(ggplot2)
library(colorspace)


data<- read.csv("/Users/Desktop/Manuscripts/STAR_protocol_IFT/Code/frequency.csv", sep = ",", header = T)

2. Change column names

data = rename(data, c("WT - Anterograde"="WT_A", "WT - Retrograde"="WT_R", "wdr-31;elmd-1;rpi-2 - Anterograde"="T_A",
                      "wdr-31;elmd-1;rpi-2 - Retrograde"="T_R"))

3. Distrupt columns with column names using pivot_longer() function for obtaining longer dataset.

data_ <- data %>%
  pivot_longer(
    cols = c("WT - Anterograde","WT - Retrograde","wdr-31;elmd-1;rpi-2 - Anterograde",
             "wdr-31;elmd-1;rpi-2 - Retrograde"),
    names_to = "Names", 
    values_to = "Frequency",
    values_drop_na = TRUE,
  )

4. Reorder columns using levels paramater.

 data_$Names <- factor(data_$Names, levels = c("WT - Anterograde", "wdr-31;elmd-1;rpi-2 - Anterograde", 
                                             "WT - Retrograde", "wdr-31;elmd-1;rpi-2 - Retrograde"))

5. Generate boxplot using ggplot() and geom_boxplot() functions with detailed theme setting e.g. removing backgrounnd colour or border, giving names to x- and y- axis.

data_ %>%
 ggplot(aes(x=Names, y=Frequency, fill= Names))+
 geom_boxplot(aes(color = Names,
                  fill = after_scale(desaturate(lighten(color, 0.6), .3))),
              size = 1) +
 scale_color_brewer(palette = "Set2") +
 geom_jitter(width=0.15, alpha=0.5)+
 theme(axis.line = element_line(colour = "Black"),
       panel.grid.major = element_line(colour = "White"),
       panel.grid.minor = element_line(colour = "White"),
       panel.border = element_blank(),
       panel.background = element_blank(),
       axis.text.x=element_blank(),
       axis.ticks.x=element_blank()) +
 labs( y = "Frequency (Particle/Sec)") +
 ylim(0,1.5)

6. Add statical analysis to graph between the reference group and samples using stat_compare_means() function.

stat_compare_means(comparisons = list(c("WT - Anterograde", "wdr-31;elmd-1;rpi-2 - Anterograde")),
                    label = "p.signif" )  +  
 stat_compare_means(label.y = 1.4, label.x.npc = "left") +
 stat_compare_means(comparisons = list(c("WT - Retrograde", "wdr-31;elmd-1;rpi-2 - Retrograde")),
                    label = "p.signif") +
 stat_compare_means(label.y = 1.3, label.x.npc = "center")