In rasilab/rasilabRtemplates: Loads Templates For Rasi Lab Use

knitr::opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE)

Analysis Instructions

This is an example outline of how we analyze data in our lab.
When you have finished the current round of analysis, use the Knit to github_document button in the tool bar above to generate a regular .md file and any associated image files.
Commit the .Rmd, .md and the _files folder to the lab Github repo.
Use scale_color_manual(values = cbPalette) and scale_fill_manual(values = cbPalette) for all plots. cbPalette is exported by the rasilabRtemplates package.

Import libraries

# string manipulation functions
library(stringr)
# standard analysis and plotting functions, includes dplyr, ggplot2 
library(tidyverse)
# loads lab default ggplot2 theme and provides color-blind friendly palette
library(rasilabRtemplates)

Import data

data <- read_csv("https://github.com/tidyverse/readr/raw/master/inst/extdata/mtcars.csv") %>% 
  print()

Transform data

processed_data <- data %>% 
  filter(am == 1) %>%
  select(mpg, qsec, carb)

processed_data %>% 
  knitr::kable()

Plot data

processed_data %>% 
  gather(statistic, value, -carb) %>% 
  ggplot(aes(x = carb, y = value, color = statistic)) +
  facet_wrap(~ statistic, ncol = 2) +
  geom_jitter(width = 0) +
  scale_color_manual(values = cbPalette)