Reproducible image-based profiling with Pycytominer.

ABSTRACT: 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.

SUBMITTER: Serrano E 

PROVIDER: S-EPMC12121495 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature