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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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Autores principales: Caicedo, Juan C, Cooper, Sam, Heigwer, Florian, Warchal, Scott, Qiu, Peng, Molnar, Csaba, Vasilevich, Aliaksei S, Barry, Joseph D, Bansal, Harmanjit Singh, Kraus, Oren, Wawer, Mathias, Paavolainen, Lassi, Herrmann, Markus D, Rohban, Mohammad, Hung, Jane, Hennig, Holger, Concannon, John, Smith, Ian, Clemons, Paul A, Singh, Shantanu, Rees, Paul, Horvath, Peter, Linington, Roger G, Carpenter, Anne E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6871000/
https://www.ncbi.nlm.nih.gov/pubmed/28858338
http://dx.doi.org/10.1038/nmeth.4397
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author Caicedo, Juan C
Cooper, Sam
Heigwer, Florian
Warchal, Scott
Qiu, Peng
Molnar, Csaba
Vasilevich, Aliaksei S
Barry, Joseph D
Bansal, Harmanjit Singh
Kraus, Oren
Wawer, Mathias
Paavolainen, Lassi
Herrmann, Markus D
Rohban, Mohammad
Hung, Jane
Hennig, Holger
Concannon, John
Smith, Ian
Clemons, Paul A
Singh, Shantanu
Rees, Paul
Horvath, Peter
Linington, Roger G
Carpenter, Anne E
author_facet Caicedo, Juan C
Cooper, Sam
Heigwer, Florian
Warchal, Scott
Qiu, Peng
Molnar, Csaba
Vasilevich, Aliaksei S
Barry, Joseph D
Bansal, Harmanjit Singh
Kraus, Oren
Wawer, Mathias
Paavolainen, Lassi
Herrmann, Markus D
Rohban, Mohammad
Hung, Jane
Hennig, Holger
Concannon, John
Smith, Ian
Clemons, Paul A
Singh, Shantanu
Rees, Paul
Horvath, Peter
Linington, Roger G
Carpenter, Anne E
author_sort Caicedo, Juan C
collection PubMed
description 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.
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spelling pubmed-68710002019-11-25 Data-analysis strategies for image-based cell profiling Caicedo, Juan C Cooper, Sam Heigwer, Florian Warchal, Scott Qiu, Peng Molnar, Csaba Vasilevich, Aliaksei S Barry, Joseph D Bansal, Harmanjit Singh Kraus, Oren Wawer, Mathias Paavolainen, Lassi Herrmann, Markus D Rohban, Mohammad Hung, Jane Hennig, Holger Concannon, John Smith, Ian Clemons, Paul A Singh, Shantanu Rees, Paul Horvath, Peter Linington, Roger G Carpenter, Anne E Nat Methods Article 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. Nature Publishing Group US 2017-09-01 2017 /pmc/articles/PMC6871000/ /pubmed/28858338 http://dx.doi.org/10.1038/nmeth.4397 Text en © The Author(s) 2017 This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Caicedo, Juan C
Cooper, Sam
Heigwer, Florian
Warchal, Scott
Qiu, Peng
Molnar, Csaba
Vasilevich, Aliaksei S
Barry, Joseph D
Bansal, Harmanjit Singh
Kraus, Oren
Wawer, Mathias
Paavolainen, Lassi
Herrmann, Markus D
Rohban, Mohammad
Hung, Jane
Hennig, Holger
Concannon, John
Smith, Ian
Clemons, Paul A
Singh, Shantanu
Rees, Paul
Horvath, Peter
Linington, Roger G
Carpenter, Anne E
Data-analysis strategies for image-based cell profiling
title Data-analysis strategies for image-based cell profiling
title_full Data-analysis strategies for image-based cell profiling
title_fullStr Data-analysis strategies for image-based cell profiling
title_full_unstemmed Data-analysis strategies for image-based cell profiling
title_short Data-analysis strategies for image-based cell profiling
title_sort data-analysis strategies for image-based cell profiling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6871000/
https://www.ncbi.nlm.nih.gov/pubmed/28858338
http://dx.doi.org/10.1038/nmeth.4397
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