Caicedo, J. C. and Cooper, S. and Heigwer, F. and Warchal, S. and Qiu, P. and Molnár, Csaba and Horváth, Péter (2017) Data-analysis strategies for image-based cell profiling. NATURE METHODS, 14 (9). pp. 849-863. ISSN 1548-7091
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Abstract
Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Tissue Array Analysis/*methods; Pattern Recognition, Automated/*methods; Microscopy/*methods; machine learning; Image Interpretation, Computer-Assisted/*methods; Humans; High-Throughput Screening Assays/*methods; Data Interpretation, Statistical; Cell Tracking/*methods; Animals; Algorithms |
| Subjects: | Q Science / természettudomány > Q1 Science (General) / természettudomány általában |
| SWORD Depositor: | MTMT SWORD |
| Depositing User: | MTMT SWORD |
| Date Deposited: | 23 Jan 2018 15:08 |
| Last Modified: | 23 Jan 2018 15:08 |
| URI: | http://real.mtak.hu/id/eprint/73142 |
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