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index.Rmd
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---
title: "Programming and Tidy Data Analysis in R"
output:
html_document:
theme: cerulean
css: style.css
---
<br>
These are the course notes for the [Monash Data Fluency](https://www.monash.edu/data-fluency)'s "Programming and Tidy data analysis in R" course. This is an intermediate level R workshop, for people wishing to increase their fluency in R. It covers tasks that while not specifically involved in statistical analysis are necessary when working with data: loading data and getting it into a form that is easy to work with, automating repetitive tasks, identifying problems such as the need for normalization and transformation, and properly understanding the story the data wants to tell.
## Slides
* [Introduction](slides/introduction.html) ([.Rmd](slides/introduction.Rmd))
## Topics
* [Programming](topics/programming.html) ([.Rmd](topics/programming.Rmd))
* [Communicating your results](topics/communication.html) ([.Rmd](topics/communication.Rmd))
* [The Tidyverse: dplyr, ggplot2, and friends](topics/tidyverse.html) ([.Rmd](topics/tidyverse.Rmd))
## Setup
This workshop is designed to work [Posit Cloud](https://posit.cloud/). Monash users can log in to Posit Cloud with their Monash google account. You can also use R and RStudio on your own laptop.
Create a new project, either in Posit Cloud or RStudio on your own laptop, then run the R code below. This will download files and install packages used in this workshop. If using R on your own laptop, then to use [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) you will need to have installed Java, and the FastQC steps will probably need some adjustments for Windows computers (this isn't an essential part of the workshop).
```{r eval=FALSE}
# Download workshop files
download.file(
"https://monashdatafluency.github.io/r-progtidy/r-progtidy-files.zip",
"r-progtidy-files.zip")
unzip("r-progtidy-files.zip")
# Download FastQC software
download.file(
"https://www.bioinformatics.babraham.ac.uk/projects/fastqc/fastqc_v0.11.8.zip",
"fastqc_v0.11.8.zip")
unzip("fastqc_v0.11.8.zip")
system("chmod u+x FastQC/fastqc")
# Install tidyverse packages and rmarkdown
install.packages(c("tidyverse", "rmarkdown"))
# Optional: install some further packages
# (these are mentioned but not essential to the workshop)
install.packages(c("devtools", "usethis", "BiocManager"))
BiocManager::install("edgeR")
```
## Files
The workshop files downloaded by the setup instructions above are also available here:
* [r-progtidy-files.zip](r-progtidy-files.zip)
## See also
* [R workshop material from Monash Data Fluency](https://www.monash.edu/data-fluency/workshops)
* [Monash Data Fluency](https://www.monash.edu/data-fluency)
* [Monash Bioinformatics Platform](https://www.monash.edu/researchinfrastructure/bioinformatics)
* [Next steps](https://monashdatafluency.github.io/r-intro-2/next-steps.html)
<br>
* ["R for Data Science" by Garret Grolemund and Hadley Wickham](https://r4ds.had.co.nz/)
* [Hadley Wickham's website](http://hadley.nz/) has further useful resources.
* [The official R manuals](https://cran.r-project.org/manuals.html) give a complete description of the R language.
## Authors
This course was developed by Paul Harrison and Richard Beare for [Monash Data Fluency](https://www.monash.edu/data-fluency) and the [Monash Bioinformatics Platform](https://www.monash.edu/researchinfrastructure/bioinformatics).
<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="figures/CC-BY.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.
## Source code
* [GitHub repository](https://github.com/MonashDataFluency/r-progtidy)