Treffer: Reproducible image-based profiling with Pycytominer.

Title:
Reproducible image-based profiling with Pycytominer.
Authors:
Serrano E; Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA., Chandrasekaran SN; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Bunten D; Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA., Brewer KI; Independent Researcher, San Francisco, CA, USA., Tomkinson J; Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA., Kern R; Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA.; Case Western Reserve University, Cleveland, OH, USA., Bornholdt M; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Fleming SJ; Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Pei R; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Arevalo J; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Tsang H; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Rubinetti V; Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA., Tromans-Coia C; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Becker T; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Weisbart E; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Bunne C; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Kalinin AA; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Senft R; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Taylor SJ; Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA., Jamali N; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Adeboye A; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Abbasi HS; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Goodman A; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Genentech gRED, South San Francisco, CA, USA., Caicedo JC; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.; Morgridge Institute for Research, University of Wisconsin-Madison, Madison, WI, USA., Carpenter AE; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Cimini BA; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA., Singh S; Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA. shantanu@broadinstitute.org., Way GP; Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA. gregory.way@cuanschutz.edu.
Source:
Nature methods [Nat Methods] 2025 Apr; Vol. 22 (4), pp. 677-680. Date of Electronic Publication: 2025 Mar 03.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Nature Pub. Group Country of Publication: United States NLM ID: 101215604 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1548-7105 (Electronic) Linking ISSN: 15487091 NLM ISO Abbreviation: Nat Methods Subsets: MEDLINE
Imprint Name(s):
Original Publication: New York, NY : Nature Pub. Group, c2004-
MeSH Terms:
Image Processing, Computer-Assisted*/methods , Software* , Single-Cell Analysis*/methods , Computational Biology*/methods, Algorithms ; Humans ; Machine Learning ; Reproducibility of Results ; Microscopy/methods
Comments:
Update of: ArXiv. 2024 Jul 2:arXiv:2311.13417v2.. (PMID: 38045474)
References:
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Grant Information:
T15 LM009451 United States LM NLM NIH HHS; RGY0081/2019 Human Frontier Science Program (HFSP); Data Science Internship Program Massachusetts Life Sciences Center (MLSC); R35 GM122547 United States GM NIGMS NIH HHS; Bits to Bytes Capital Call Massachusetts Life Sciences Center (MLSC); T15LM009451 U.S. Department of Health & Human Services | NIH | U.S. National Library of Medicine (NLM)
Entry Date(s):
Date Created: 20250303 Date Completed: 20250408 Latest Revision: 20251002
Update Code:
20251002
PubMed Central ID:
PMC12121495
DOI:
10.1038/s41592-025-02611-8
PMID:
40032995
Database:
MEDLINE

Weitere Informationen

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.
(© 2025. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Competing interests: The authors declare no competing interests.