Engineering/Learn

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Learn

On this page you will find information on: Analyzing and Plotting Data.

Introduction

Now that you’ve finished running your Tests, it’s time to analyze your data and learn from your work.

Analyzing and Plotting Data

Presenting your data correctly and well is just as important as good measurement. Below are some tools that can help you analyze your data and create useful plots to explain your results. There is an older but still very pertinent article here on things to consider when plotting your data: "Some Helpful Hints in Preparing Scientific-Quality Plots for Reports by hand or by using Excel." We also recommend teams look at our Exemplary Projects page to see good past iGEM examples. This also has examples of many common graphs and figures, presented in published scientific articles.

Fiji

Fiji, a distribution of ImageJ, is a powerful, free program that is widely used to explore, process, and analyze fluorescence microscopy data. With a scripting language and a large community of users, plugins exist to meet many image processing and analysis goals, and new extensions of the software can easily be written.

Image from DNAplotlib

DNAplotlib

Visually integrating graphs of your data with a schematic representation of the parts and circuits which generated that data is an important aspect of scientific communication in synthetic biology. There are many ways to achieve this goal, but for teams with proficiency in the Python programming language, DNAplotlib is an excellent tool developed by the authors of Der and Glassey et al., 2016, ACS Synthetic Biology for this purpose. Even for teams without coding experience, we recommend looking at some of DNAplotlib’s sample graphs as an example of good data visualization practices in synthetic biology.

Image from WebPlotDigitizer

WebPlotDigitizer

Often, published data (whether in scientific papers or in the BioBrick Registry) exists only in graphical form, which prevents you from being able to make quantitative comparisons between your results and existing work. WebPlotDigitizer, developed by Ankit Rohatgi, is an open-source web-based tool that solves this problem by allowing you to input an image of a graph or plot and returning numerical values for the data depicted in the image. No coding experience is required-- just upload an image, define values along the axes, and click on points within the graph to generate a table of data that you can analyze!

R and R Studio

R studio is a free set of tools designed to let you use the programming language R in an easy and effective way. R is a programming language for statistical computing which can be used to analyse data from your experiments, and plot graphs for use on your wiki. As R is an opensource platform, scripts written to analyse and plot your data can be uploaded to iGEM wikis, which helps others better understand your data and hence more likely to use aspects of your project. A beginners tutorial for R can be found here.

Have a resource to contribute?

Please email the Engineering Committee at engineering [AT] igem [DOT] org and provide links to material with a short description. We’ll check it out and if we believe it will be helpful, we’ll add it to this page!