BINF8750-Data-Viz

Graduate course on "Data Visualization for Life Sciences Research". This course will explore best practices for data visualization across biomedical and life science disciplines. Through hands-on exercises and real-world case studies, students will develop skills for displaying research data in compelling visual formats. Emphasis will be placed on translating data into compelling narratives that resonate with diverse audiences, with a particular focus on developing informative figures for peer- reviewed manuscripts and scientific presentations.

This course uses material from the following two textbooks:

• Wilke, Claus O. (2019) Fundamentals of Data Visualization: A primer on making informative and compelling figures, O’Reilly Publishing. E-Book freely available here: https://clauswilke.com/dataviz/
• Healy, Kieran (2026) Data Visualization: A practical introduction 2nd Edition, Princeton University Press. E-book freely available here: https://socviz.co/

Course Schedule:

• Week 1 - Class introductions; The good, the bad, and the ugly of data visualizations; software tools.
• Week 2 - Telling a story and making a point
• Week 3 - Aesthetics, “branding”, and types of data
• Week 4 - Color and Accessibility
• Week 5 - Whitespace, captions, and typography
• Week 6 - A tour of scientific plot types (part 1)
• Week 7 - A tour of scientific plot types (part 2)
• Week 8 - Maps and geospatial data visualizations
• Week 9 - Plot reproducibility and coding considerations: R markdown, ggplot, Quarto, version control
• Week 10 - Final Presentations

Room Change - we will be in Davison C130 on Feb 20th due to ILS interviews in our normal classroom

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Class resources - links shared during class:

• Coolors - quick way to generate custom color palettes - https://coolors.co/
• R color palette finder - https://r-graph-gallery.com/color-palette-finder
• I want hue (another color palette finder) - https://medialab.github.io/iwanthue/
• Color vision deficiency simulator - https://www.color-blindness.com/coblis-color-blindness-simulator/
• Coloring for Colorblindness - https://davidmathlogic.com/colorblind/#%23D81B60-%231E88E5-%23FFC107-%23004D40
• Who Can Use (tool that checks for common color vision deficiency and contrast issues) - https://www.whocanuse.com/
• Procreate (user friendly drawing app, you can also use it to create icons) - https://procreate.com/
• ggOceans (R package for creating ocean bathymetric maps) - https://mikkovihtakari.github.io/ggOceanMaps/
• marMap (another R package for creating bathymetric maps) - https://github.com/ericpante/marmap

Other resources that may be useful:

• On campus graphic design services available through the college of Vet Med - https://vet.uga.edu/erc/portfolio/design/

Additional textbooks that may be useful:

• Data Integration, Manipulation and Visualization of Phylogenetic Trees (by Guangchuang Yu) - https://yulab-smu.top/treedata-book/
• Wickham, Hadley, Mine Çetinkaya-Rundel, and Garrett Grolemund. 2023. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. 2nd ed. O’Reilly Media. https://r4ds.hadley.nz/