> For the complete documentation index, see [llms.txt](https://zhanglab-aim.gitbook.io/labwiki/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://zhanglab-aim.gitbook.io/labwiki/handbook/paper-writing.md).

# Paper writing

## Making figures

### What message does your figure aim to convey?

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### Scientific Rigor

**You Should Always Check**: include the x/y axis limits, enlarge the <mark style="color:red;">labels</mark> (axis ticks\&labels, legends; can you still read the figure at 100% on screen?), minimize unnecessary <mark style="color:red;">blank space</mark>. &#x20;

Choose the right visualization: box, bar, swarm, or dots?&#x20;

Save vectorized version of the plots whenever possible, i.e. <mark style="color:red;">PDF, SVG</mark>.

Visualize the local density for dense scatter plots.

### Multi Panel Figures&#x20;

Try to make every panel/figure as a square.&#x20;

In R's ggplot, making the canvas <mark style="color:red;">4x4 or 4.5x4.5</mark> and <mark style="color:red;">font size 11</mark> is usually a good balance between readability and density.

Use Adobe Illustrator to <mark style="color:red;">align</mark> all panels. Keep the <mark style="color:red;">same</mark> font size as above.

No panels should be squeezed or stretched!

### Overview Figure

Use <mark style="color:red;">BioRender</mark> and <mark style="color:red;">FontAwesome</mark> for free icons.

Try making your own icons/cartoons. Never paste a low-resolution image into your figure.&#x20;

You can add background color to enhance certain parts in the overview; choose low saturation colors.

### Color Scheme

Avoid using the <mark style="color:red;">default</mark> seaborn/ggplot colors. Just don't.

The tip that always works: go to the <mark style="color:red;">journal</mark> you're submitting to, browse a few papers to get a <mark style="color:red;">taste</mark>.

For two-way contrasts: navyblue vs orange; red vs black; orange vs grey.

For three-way contrasts: green vs orange vs blue; blue vs purple vs green.

For heatmap: if center is zero and is meaningful, blue - white - red. otherwise consider blue-yellow.