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. 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.

We updated: Figures (e.g., remove panel from Figure 1) to increase clarity. Consolidated the introduction, results, and discussion into a single section. Added a new analysis to predict compounds that cause undesirable cell injuries. Added three tables including one to highlight image-based profiling software limitations. 14 pages, 2 main figures, 5 supplementary figures, 3 tables