Scalable and cost-efficient gene assembly from oligopools

All data analysis in Freschlin et al. (2025)(1) is contained here.

We include a conda environment to run all analyses, but please refer to directory-specific README files for specific details. The notebooks directory reproduces all figures from the paper. ngs_processing reproduces all ngs analyses.

Create conda environment:

conda env create --file environment.yml

References

(1) Chase R. Freschlin, Kevin K. Yang, Philip A. Romero. Scalable and cost-efficient custom gene library assembly from oligopools. bioRxiv 2025.03.22.644747; doi: https://doi.org/10.1101/2025.03.22.644747