Original title: Reproducible image-based profiling with Pycytominer
Authors: Erik Serrano, Srinivas Niranj Chandrasekaran, Dave Bunten, Kenneth I. Brewer, Jenna Tomkinson, Roshan Kern, Michael Bornholdt, Stephen Fleming, Ruifan Pei, John Arevalo, Hillary Tsang, Vincent Rubinetti, Callum Tromans-Coia, Tim Becker, Erin Weisbart, Charlotte Bunne, Alexandr A. Kalinin, Rebecca Senft, Stephen J. Taylor, Nasim Jamali, Adeniyi Adeboye, Hamdah Shafqat Abbasi, Allen Goodman, Juan C. Caicedo, Anne E. Carpenter, Beth A. Cimini, Shantanu Singh, Gregory P. Way
In the world of high-throughput microscopy, capturing cell images is lightning-fast, producing heaps of data. Extracting thousands of image-based features reveals crucial single-cell traits, unveiling cell states and biological functions. However, using these features for discovery—termed image-based profiling—faces hurdles. Raw features need refining, and there’s a scarcity of scalable, reproducible open-source software.
Original article: https://arxiv.org/abs/2311.13417