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Nat Methods DOI:10.1038/nmeth.4397

Data-analysis strategies for image-based cell profiling.

Publication TypeJournal Article
Year of Publication2017
AuthorsCaicedo, JC, Cooper, S, Heigwer, F, Warchal, S, Qiu, P, Molnar, C, Vasilevich, AS, Barry, JD, Bansal, HSingh, Kraus, O, Wawer, M, Paavolainen, L, Herrmann, MD, Rohban, M, Hung, J, Hennig, H, Concannon, J, Smith, I, Clemons, PA, Singh, S, Rees, P, Horvath, P, Linington, RG, Carpenter, AE
JournalNat Methods
Volume14
Issue9
Pages849-863
Date Published2017 Aug 31
ISSN1548-7105
KeywordsAlgorithms, Animals, Cell Tracking, Data Interpretation, Statistical, High-Throughput Screening Assays, Humans, Image Interpretation, Computer-Assisted, Machine Learning, Microscopy, Pattern Recognition, Automated, Tissue Array Analysis
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.

DOI10.1038/nmeth.4397
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/28858338?dopt=Abstract

Alternate JournalNat. Methods
PubMed ID28858338
Grant ListU54 GM114833 / GM / NIGMS NIH HHS / United States