Skip to content

LAMetskas/2025_polymerizationAnalysis

 
 

Repository files navigation

tomoPoseLink is a script package written by the Metskas Lab at Purdue University. It requires a Matlab license to run, though users are welcome to convert code to Julia under share-and-share-alike guidelines.

Installation

tomoPoseLink requires MATLAB and a Dynamo installation (www.dynamo-em.org). It will run on any operating system and hardware configuration.

tomoPoseLink is adapted from a precursor collection of ObservableHQ (JavaScript) modules that were translated to MATLAB and then further developed. The new MATLAB script package is hosted online in GitHub for version control. To compile from the source using git, follow the steps outlined below:

  1. git clone https://github.com/LAMetskas/2025_polymerizationAnalysis.git
  2. cd MetskasLab
  3. run your MATLAB executable
  4. In MATLAB command window: run <DYNAMO_ROOT>/dynamo_activate.m
  5. Run scripts using the command window

Quick-start Guide

Inputs:

  • Dynamo-formatted table from a subtomogram averaging project
  • Particle diameter
  • Pixel size of tomogram

Outputs:

  • Matlab object file with information on carboxysomes
  • Dynamo-formatted particle tables
  • csv file with information on each particle's behavior
  • plots and graphics according to user choices

Simply run the main.m script in Matlab, which will call the base functions in order and guide user through inputs and choices.

Full Documentation

Full documentation of all scripts and the script hierarchy is available in the Documentation.pdf file, and should be consulted prior to serious use.

Disclaimers and licenses

Users agree to use the script package as is; we to not guarantee assistance, user support, or updates as new software versions are introducted.

https://github.com/LAMetskas/2025_polymerizationAnalysis/ This package is provided under Creative Commons copyright license Attribution-NonCommercial-ShareAlike 4.0 International (https://creativecommons.org/licenses/by-nc-sa/4.0/).

This copyright license allows use for noncommercial use only, with attribution to the original package and sharing of all changes under the same license as the original. We do not permit use of the code for AI training purposes unless the final AI model/tool will be provided under the same open-access copyright license, without any restrictions including logins or paywall.

About

Scipt package to accompany 2025 BMC Methods manuscript submission

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages

  • MATLAB 94.2%
  • JavaScript 5.7%
  • Other 0.1%