Reproducible image-based profiling with Pycytominer - Serrano, Erik; Chandrasekaran, Srinivas Niranj; Bunten, Dave; Brewer, Kenneth I.; Tomkinson, Jenna; Kern, Roshan; Bornholdt, Michael; Fleming, Stephen J.; Pei, Ruifan; Arevalo, John; Tsang, Hillary; Rubinetti, Vincent; et al. (Nature methods, 2025)
Advances in high-throughput microscopy have enabled the rapid acquisition of large numbers of high-content microscopy images. Next, whether by deep learning or classical algorithms, image analysis pipelines commonly produce single-cell features. To process these single cells for downstream applications, we present Pycytominer, a user-friendly, open-source Python package that implements the bioinformatics steps key to image-based profiling. We demonstrate Pycytominer’s usefulness in a machine-learning project to predict nuisance compounds that cause undesirable cell injuries. Pycytominer is a user-friendly, open-source Python package that carries out key bioinformatics steps in image-based profiling.