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https://swcarpentry.github.io/r-novice-inflammation/

Programming with R
https://swcarpentry.github.io/r-novice-inflammation/

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Programming with R

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# r-novice-inflammation



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[The Carpentries](https://carpentries.org/) teach foundational coding, and data science skills to

researchers worldwide. This GitHub repository generates the Software Carpentry lesson website

"Introduction to R for non-programmers using inflammation data." The [lesson website can be viewed

here][online]. Making changes in this GitHub repository

allows us to change the content of the lesson website.



The following people are maintainers for this lesson, and are responsible for determining which

changes to incorporate into the lesson:



- [Rohit Goswami](https://carpentries.org/instructors/#HaoZeke) (@haozeke)

- [Hugo Gruson](https://carpentries.org/instructors/#bisaloo) (@Bisaloo)

- [Isaac Jennings](https://carpentries.org/maintainers/#isaac-jennings) (@isaac-jennings)



Alumni:



- [Daniel Chen](https://software-carpentry.org/team/#chen_daniel) (@chendaniely)

- [Diya Das](https://diyadas.github.io) (@diyadas)

- [Katrin Leinweber](https://carpentries.org/instructors/#katrinleinweber) (@katrinleinweber)



The goal of this lesson is to teach novice programmers to write modular code to

perform a data analysis. R is used to teach these skills because it is a

commonly used programming language in many scientific disciplines. However, the

emphasis is not on teaching every aspect of R, but instead on

language agnostic principles like automation with loops and encapsulation with

functions (see [Best Practices for Scientific Computing][best-practices] to

learn more). This lesson is a translation of the [Python version][py],

and is also available in [MATLAB].



The example used in this lesson analyzes a set of 12 data files with

inflammation data collected from a trial for a new treatment for arthritis (the

data was simulated). Learners are shown how it is better to create a function

and apply it to each of the 12 files using a loop instead of using copy-paste

to analyze the 12 files individually.



## Contributing



We value your contributions. How to contribute to this lesson is outlined in

[CONTRIBUTING.md](https://github.com/swcarpentry/r-novice-inflammation/blob/master/CONTRIBUTING.md).

If you have questions about our contributing guidelines, please create a new issue in the [issues]

tab and one of the maintainers will respond.



## Getting Help



Please see [https://github.com/carpentries/lesson-example](https://github.com/carpentries/lesson-example)

for instructions on formatting, building, and submitting lessons,

or run `make` in this directory for a list of helpful commands.



If you have questions or proposals, please send them to the [r-discuss] mailing list.



[online]: https://swcarpentry.github.io/r-novice-inflammation/

[best-practices]: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745

[py]: https://github.com/swcarpentry/python-novice-inflammation

[MATLAB]: https://github.com/swcarpentry/matlab-novice-inflammation

[issues]: https://github.com/swcarpentry/r-novice-inflammation/issues

[r-discuss]: https://carpentries.topicbox.com/groups/discuss