Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes
Chadwick T Davis,
Sigrun M Gustafsdottir,
Christopher C Gibson,
Anne E. Carpenter
Posted 25 Apr 2016
bioRxiv DOI: 10.1101/049817 (published DOI: 10.1038/nprot.2016.105)
Posted 25 Apr 2016
In morphological profiling, quantitative data are extracted from microscopy images of cells to identify biologically relevant similarities and differences among samples based on these profiles. This protocol describes the design and execution of experiments using Cell Painting, a morphological profiling assay multiplexing six fluorescent dyes imaged in five channels, to reveal eight broadly relevant cellular components or organelles. Cells are plated in multi-well plates, perturbed with the treatments to be tested, stained, fixed, and imaged on a high-throughput microscope. Then, automated image analysis software identifies individual cells and measures ~1,500 morphological features (various measures of size, shape, texture, intensity, etc.) to produce a rich profile suitable for detecting subtle phenotypes. Profiles of cell populations treated with different experimental perturbations can be compared to suit many goals, such as identifying the phenotypic impact of chemical or genetic perturbations, grouping compounds and/or genes into functional pathways, and identifying signatures of disease. Cell culture and image acquisition takes two weeks; feature extraction and data analysis take an additional 1-2 weeks.
- Downloaded 3,201 times
- Download rankings, all-time:
- Site-wide: 1,639 out of 89,518
- In systems biology: 38 out of 2,311
- Year to date:
- Site-wide: 14,784 out of 89,518
- Since beginning of last month:
- Site-wide: 17,509 out of 89,518
Downloads over time
Distribution of downloads per paper, site-wide
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!