Programs

Feel free to download, edit and re-upload any of the programs here to any website, or your own wiki, for your own purposes. All of the content here (as in all of IGEM) is open source.

TECAN Plate Reader
A serious issue that we faced whilst analysing our results was the speed and accuracy at which we could take the raw data from experiments and extract the information we needed. One of our most used pieces of equipment was the tecan plate reader. Each time a new reading came in, one of the team would laboriously sit for hours copying the raw text over to excel and then picking through sheets of numbers sorting out technical and biological replicates before graphing. Each time the same formulas would be rewritten and each time errors would be untraceable and set the whole process back to the beginning. This would have to be done with both Fluorescence and Optical Density making the task twice as long again. Seeing as one of the main constraints of this project is time we needed a solution to the problem that would improve efficiency and accuracy. Having been working on Matlab, the team soon got to grips with the built in excel read/write functions and so Analyse.m was born.

The idea for the program was to output an expected value and standard deviation over all technical replicates of an experiment, and then to take those figures and give an average over the bigger data set of all biological replicates, as well as the standard error for those. This would allow us to see how each individual batch reacted over time and to disregard outliers, but it would also give a uniformity in how the information was presented. Results would no longer be presented on the mood and whimsy of the analyser. Analyse.m does exactly that.

When executed on the raw tecan data in excel format it will create new sheets inside the file and ask for which plates were inside the technical replicate, leaving the space blank indicates no other technical replicates and moves on to the next biological replication of the experiment, leaving blank twice indicates end of plates and the program terminates. Each experiment is given a name within the program and put directly into the spreadsheet. This data is then in the perfect format for our data analyst who was able to import the spreadsheets directly and graph exactly what was needed.

DE Solvers
To help with the modelling we created several solvers that went above and beyond the MATLAB functions. We developed:
- an ODE solver based on a fourth order Runge-Kutta method (RK4).
- a Time Delay system solver using fourth order Runge-Kutta methods (TDRK4).
- a Stochastic DE solver using fourth order Runge-Kutta methods (SRK4).
- a Stochastic Time Delay solver using fourth order Runge-Kutta methods (STDRK4).