3 Making figures

We’re not covering this in the workshop. But there are some resources to help with this process when you do, if you’d like the come back to this book.

3.1 Resources

3.1.1 Softwares for making figures

There are many, many different softwares for data visualization. Which one you use will depend mostly on the type of figure you want to make, and how much time you want to invest in making it.

You can use the Types of figures cheat sheet to help determine what kind of visualization you want to make.

Workflow tip!

Don’t be afraid to use different softwares for different steps of figure making.

It’s typical to start by creating a plot or image using a visualization-specific software (like Prism, excel, or FIJI). You can save or export that plot or image as a separate file (.pdf or .png usually work well here). Then you can finish making your figure by opening that saved plot in a different software (like google slides, powerpoint, or inkscape), to add labels, captions, and arrange panels.

This is because the data visualization softwares typically aren’t great at the finer points of figure making, like labeling and arranging. These tasks are easier in less specialized softwares like google slides or inkscape. But the less specialized softwares can’t make the graphs, so in practice, you end up going back and forth between them.

3.1.1.1 Plot-making software

Hot take!

Graphpad Prism is widely used for making plots and performing simple data analyses.

To make more customizable plots, work with a lot of data at a time, and perform more powerful analyses, you’ll have to learn a little bit of programming. The dominant programming language for visualizing data is R, and the ggplot2 package.

Start with these

These softwares are powerful, but take time to learn

3.1.1.2 Scheme-making software

Start with these

These softwares are powerful, but take time to learn

3.1.1.3 Image analysis software

3.1.1.4 Protein structure visualization software

3.2 Activity

To get started on your figure, try filling out the guides for figure reading in Section 2.2.2 for each panel you plan to make. You want a reader of your figure to be able to find everything necessary to fill out the whole guide easily. Figure captions can include key details on how an experiment was set up, to help readers understand how the values presented on the axes relate to the scientific question.

Before getting started, ask your research mentor if they have a specific data visualization software they would like you to use.