How to visualize the generated secondary structure of RNA

Question

I am working on a tool for visualizing the secondary structure of RNA, for this purpose I implemented the Nussinov algorithm, which generates the secondary structure of RNA as a list with the corresponding indices, the code can be found here [0]

[0] http://dpaste.com/596262/

But I really had an understanding of how I should visualize it (like a planar graph), the code above gives me a consistent list of secondary structure, so that someone can offer me how I can visualize the structure. an example of such a tool can be found here [1]

[1] http://rna.tbi.univie.ac.at/cgi-bin/RNAfold.cgi

and I know that there are better algorithms, but for now I just want to visualize this, and as soon as I understand the visualization, I will go for the best algorithm.

Answer 1

You can do this with jmol. Jmol allows you to add arbitrary bonds / atoms to the coordinate space using its java or I believe its javascript api as well.

In general, of course, PDB file formats will be used for such data.

Answer 2

RNAviz is old, but still widely used. JalView , apparently, was supposed to get a renovation of the secondary structure of RNA through the GSoC project last year, but I'm not sure what status the program has.

Answer 3

Visualization of the secondary structure of RNA (or any graph, for that matter) is algorithmically a complex problem. You need to make sure that there are as few overlaps as possible while maintaining consistent link lengths. As the other answers pointed out, there are a number of existing implementations that you can already use. I'll just add another one that is fairly easy to use and does not require a download:

forna - nibiru.tbi.univie.ac.at/forna

Here you just need to enter a dot chain string:

>molecule_name CGCUUCAUAUAAUCCUAAUGAUAUGGUUUGGGAGUUUCUACCAAGAGCCUUAAACUCUUGAUUAUGAAGUG ((((((((((..((((((.........))))))......).((((((.......))))))..))))))))) 

This will give you a visualization that looks something like this:

This is calculated using a combination of the ViennaRNA RNAplot program and the radiation pattern algorithm using d3.