Appendix A — Contributors & acknowledgments

Authors

Affiliations

Sean Davis

University of Colorado
Anschutz School of Medicine

Lori Shepherd Kern

Roswell Park Comprehensive Cancer Center
Bioconductor Core Team

Martin Morgan

Roswell Park Comprehensive Cancer Center
Bioconductor Core Team

This book is the work of many hands, and it stands on a great deal of generously shared material. Individual chapters carry their own author bylines; this page is the single place that credits everyone — and every adapted source — across the whole book.

A.1 Authors

People who wrote or substantially shaped material that appears in the book:

• Sean Davis (University of Colorado Anschutz School of Medicine) — primary author and editor; most chapters.
• Lori Shepherd Kern (Roswell Park Comprehensive Cancer Center; Bioconductor Core Team) — Base R versus the tidyverse, Control statements, Factors, Organizing, saving, and loading your work, and edits throughout.
• Martin Morgan (Roswell Park Comprehensive Cancer Center; Bioconductor Core Team) — Base R versus the tidyverse, and much of the BRFSS case study.
• Stephen Turner — the dplyr introduction and the Data Frames dataset and material, adapted from his Bioconnector tutorials.
• Garrett Grolemund — the dice/first-steps material in R Basics and Packages and dice, and several data-structure figures, adapted from Hands-On Programming with R (see below).

A.2 Adapted material and sources

Several chapters build on openly shared teaching resources. We are grateful to their authors. Where a source carries a license, it is noted; material adapted from those sources remains under its original license.

• Garrett Grolemund, Hands-On Programming with R (CC BY-NC-ND) — dice examples and figures (hopr_*) in the early R chapters.
• Robert Kabacoff, Modern Data Visualization with R (CC BY-NC 4.0) — the basis of the ggplot2 chapter.
• Stephen Turner, Bioconnector tutorials — the Data Frames and dplyr material and example data.
• Alboukadel Kassambara / STHDA, penalized-regression tutorial — part of the Models (machine-learning) chapter.

NoteA note on licensing

Most of this book is released under CC0. The adapted material and figures listed above are the exceptions: they retain the original CC BY-NC or CC BY-NC-ND licenses of their sources and are used here with attribution. We are working toward replacing those with original or openly-licensed equivalents so the whole book is uniformly open.

A.3 Datasets

The book reuses several published datasets, cited in the chapters that use them — among them the Brauer et al. (2008) yeast growth-rate study (via the Bioconnector tutorials), the DeRisi et al. (1997) diauxic-shift time course, the airway RNA-seq dataset (Himes et al.), GEO accession GSE103512, ENCODE CTCF peaks (ENCFF960ZGP), a DNA-methylation dataset from a Galaxy tutorial, and curated microbiome and single-cell datasets from Bioconductor data packages. Datasets we redistribute are vendored under data/; figure sources are recorded in images/README.md.

A.4 Tools

Built with Quarto, R, and Bioconductor, and published openly so others can read, reuse, and contribute.

A.5 Contributing

Corrections, suggestions, and contributions are welcome through the GitHub repository — open an issue or a pull request. If you contribute material, you’ll be credited here and in the relevant chapter.