  Advances in high-throughput microscopy have enabled the rapid acquisition of
large numbers of high-content microscopy images. Whether by deep learning or
classical algorithms, image analysis pipelines then 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, known as image-based profiling. We demonstrate
Pycytominers usefulness in a machine learning project to predict nuisance
compounds that cause undesirable cell injuries.
