NOTE. This collection of scripts and macros has been developed for the following publication:
Four ways of implementing robustness quantification in strain characterisation.
Torello Pianale, L., Caputo, F. & Olsson, L. Biotechnol Biofuels 16, 195 (2023).
https://doi.org/10.1186/s13068-023-02445-6
Collection of scripts to analyse:
- BioLector I data coming from multiple screenings. For analysing of individual screenings, please check ScEnSor Kit Scripts (https://github.com/lucatorep/ScEnSor-Kit-Scripts).
- Flask data coming from Scientific Bioprocessing biomass monitoring, but easily adapted to other setups + HPLC data.
- Microscopy images (preprocessing and biosensor output).
Getting started:
- Install R (https://cran.r-project.org/), RStudio (https://posit.co/download/rstudio-desktop/) and then the RMarkdown package in R (https://rmarkdown.rstudio.com/). No need to pre-install other packages needed for the scripts as they will be installed automatically (if they are not already).
- Install Fiji (Fiji: https://imagej.net/software/fiji/downloads), if microscopy images need to be analysed.
- Always check the data organisation in the example files provided.
- Follow the directions in the scripts and macros (details before each chunk and important sections of scripts).
- Make changes upon need (replace grouping variables, way of importing data, etc.).
Luca Torello Pianale, lucat@chalmers.se
Chalmers University of Technology, Department of Life Sciences, Industrial Biotechnology Division.
Created: October, 2023.
The scripts were tested with:
- R Version 4.3.1 (2021-11-01)
- RStudio (2021.09.2 Build 382)
- ImageJ 1.53t
Acknowledgment of support: This material is based upon work supported by the Novo Nordisk Foundation grant DISTINGUISHED INVESTIGATOR 2019 - Research within biotechnology-based synthesis & production (#0055044).