Adding code to manuscript

[Patrik]

I'm done writing a manuscript and I'm wondering what's the best way to incorporate the code used for data analyses and figures. I would like the entire paper to be completely reproducible. Suggestions?

I thought about splitting up the code into R Markdown files that I can refer to in the Results section as Supporting Information. 

Thanks a lot.

Patrik

[Matthew D Pagel]

In the past I've used a DOI service to make my code able to be cited by others (and myself). This makes sure the code is a "snapshot" of a given point in time, so that even if you later make modifications to your code, someone else can exactly reproduce your results (assuming the same input data). Of course, you can also maintain an updated "fork" of your code elsewhere.

For example, http://dx.doi.org/10.5281/zenodo.20043 points to https://github.com/MPagel/readseq/tree/v2.02, but I've made one additional modification to my main branch at github.../readseq/

(so zenodo is the DOI-issuer)


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[Jason Moore]

Here is an example of a computationally reproducible paper I wrote a few years back:

https://github.com/csu-hmc/perturbed-data-paper

The source for the manuscript and the source to create the figures are in the repository. After cloning the repo, you can run a simple make command to build the paper. You have to install the software dependencies first (the main package dependency is versioned and hosted on a package repository), then you can simply call make to download the raw data, run analysis, and generate the paper in one command. In the caption of each figure or table I reference the script that generates that item.

I've had a number of people build the paper on their computer to ensure it worked cross-platform. The main hassle is installing the software, which I'd alleviate in the future with a conda environment or docker image.

This is one of many ways you could can do this.

Jason
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[Myfanwy Johnston]

Related to this topic, a new paper just came out on data storage for reproducibility: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005097

Jason
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University of California at Davis

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