Data-analysis strategies for image-based cell profiling

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 involv...

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Bibliographic Details
Main Authors: Caicedo, Juan C. (Author) , Heigwer, Florian (Author)
Format: Article (Journal)
Language:English
Published: 31 August 2017
In: Nature methods
Year: 2017, Volume: 14, Issue: 9, Pages: 849-863
ISSN:1548-7105
DOI:10.1038/nmeth.4397
Online Access:Verlag, Volltext: http://dx.doi.org/10.1038/nmeth.4397
Verlag, Volltext: https://www.nature.com/articles/nmeth.4397
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Author Notes:Juan C. Caicedo, Sam Cooper, Florian Heigwer, Scott Warchal, Peng Qiu, Csaba Molnar, Aliaksei S. Vasilevich, Joseph D. Barry, Harmanjit Singh Bansal, Oren Kraus, Mathias Wawer, Lassi Paavolainen, Markus D. Herrmann, Mohammad Rohban, Jane Hung, Holger Hennig, John Concannon, Ian Smith, Paul A. Clemons, Shantanu Singh, Paul Rees, Peter Horvath, Roger G. Linington, Anne E. Carpenter
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Summary: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 Description:Gesehen am 09.04.2018
Physical Description:Online Resource
ISSN:1548-7105
DOI:10.1038/nmeth.4397