A molecular model can contain the right information and still be difficult to interpret. One common reason is color: a palette chosen for appearance alone may make separate chains look alike, hide a gradual change, or make a neutral value seem like an extreme. A useful first step is to ask what the colors are meant to communicate.
SAMSON’s default palettes are grouped into five types: discrete, sequential HCL, qualitative HCL, diverging HCL, and flexible diverging HCL. The category is a practical clue to the kind of visual distinction the palette offers. HCL means Hue-Chroma-Luminance, a color space described in the documentation.
When the goal is to distinguish categories
Use a discrete or qualitative palette when colors stand for separate groups rather than values along a scale. For example, if you want to tell several chains, regions, or other categories apart, each group needs a distinct color; there is no implied order from the first color to the last.
The discrete collection includes options such as Accent, Okabe-Ito, Paired, Set1, and tab10. Qualitative HCL palettes include Default, Pastel, Dynamic, Warm, and Cold. These are starting points for categorical colorization, not a requirement to use every color in a palette. If the scene contains only a few groups, a small, consistent subset is usually easier to scan than a long sequence of unrelated hues.
When the data has an order
For a quantity that moves from lower to higher values, a sequential palette provides a visual progression. SAMSON’s sequential HCL options include Blue, Green, Gray, Heat, Inferno, Plasma, Viridis, and several two-color or multi-color choices. Pick one that makes the direction of change legible in the context of your structure and background.
A practical check is to follow the scale from its low end to its high end and ask whether the progression is easy to understand without repeatedly checking a legend. Avoid treating a sequential palette as a set of unrelated labels: its main job is to show that values are ordered.
When a meaningful midpoint matters
If values represent two sides of a meaningful center—for example, below versus above a reference value—a diverging palette can make that structure visible. SAMSON lists diverging HCL palettes such as Berlin and Blue-Red, as well as flexible diverging palettes including RdBu, RdYlBu, PiYG, and Spectral. The key question is whether the data actually has a meaningful midpoint. If it does not, a diverging scheme can suggest a contrast that is not present in the underlying values.
A quick selection routine
- Name what color represents: separate categories, an ordered value, or values around a center.
- Choose the matching palette family: discrete or qualitative for categories, sequential for ordered values, and diverging for a meaningful midpoint.
- Inspect the result on the model: check that important regions remain distinguishable and that the colors do not compete with the structural details you need to see.
- Keep the interpretation consistent: when comparing views, use the same palette logic so that a color continues to mean the same thing.
If the palette’s direction does not suit the data, SAMSON’s palette and color scheme dialogs let you revert the left and right arms. You can also create custom HCL palettes; the Colorizing guide covers palettes in more detail.
These choices are not just decoration. Matching palette type to data type helps prevent a viewer from reading categories as a scale, or mistaking a one-directional progression for a two-sided comparison. For the full list of defaults, see Default color palettes.
Note: SAMSON and all SAMSON Extensions are free for non-commercial use. Get SAMSON.