19  Acknowledgements

For a scientific report to be completely credible, it must be reproducible. The full computational environment used to derive the results, including the data and code used for statistical analysis should be available for others to reproduce. quarto is a tool that allows you integrate your code, text and figures in a single file in order to make high quality, reproducible reports. A paper published with an included quarto file and data sets can be reproduced by anyone with a computer.

This books was first written to be a guide for a course run by the Statistics Society Australia (SSA), and Melbourne Integrative Genomics (MIG) on November 12, 2018.

I’d like to first thank Miles McBain, for his working book, “Git For Scientists”. This book inspired the structure and workflow of this existing book.

I’d also like to thank Karthik Ram, Yoav Ram, Martin Fenner, Puneet Kishor, and Jonathan Dugan, involved with the Scholarly Markdown site. This has helped inform some of the structure of this book. I’d also like to thank Patrick Robotham for his helpful discussions when first creating this book.

There have been various wonderful contributions from the community to fix typos in this book, I would like to thank Allison Presmanes Hill PR1, PR2, as well as the many offline helpful conversations about serving this book online and other matters. I’d also like to thank Murray Cadzow PR, and Federico Marini PR, and Raymond B Huey for their thoughtful contributions.