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基于图像的细胞分析中的数据分析策略。

Data-analysis strategies for image-based cell profiling.

作者信息

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

机构信息

Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.

Imperial College London, London, UK.

出版信息

Nat Methods. 2017 Aug 31;14(9):849-863. doi: 10.1038/nmeth.4397.

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.

摘要

基于图像的细胞分析是一种用于量化各种细胞群体间表型差异的高通量策略。它为通过化学和基因扰动大规模研究生物系统铺平了道路。该技术的一般工作流程包括使用高通量显微镜系统进行图像采集以及后续的图像处理和分析。在此,我们介绍从一系列显微镜图像创建高质量基于图像(即形态学)分析图谱所需的步骤。基于全球20个实验室在完善其基于图像的细胞分析方法以追求生物学发现方面的经验,我们推荐在数据分析过程的每个阶段都已证明有用的技术。推荐的技术涵盖了可能适用于各种生物学目标、实验设计和实验室偏好的替代方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c92/6871000/bf3508720b2d/41592_2017_Article_BFnmeth4397_Fig1_HTML.jpg

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