Data-analysis strategies for image-based cell profiling
By Juan C. Caicedo, Sam Cooper, Florian Heigwer, Scott Warchal, Peng Qiu, Csaba Molnar, A. Vasilevich, J. Barry, Harmanjit Singh Bansal, Oren Z. Kraus and 14 more. Nature Methods, 2017
696 citations recorded by the source corpus.
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.
Subfields: Biophysics, Media Technology, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/1e1f905c5d8c6a2ad18b09ce8eb5d2b4c6b174f5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biophysics
- Shantanu Singh
- Juan C. Caicedo
- Anne E Carpenter
- Nick Pawlowski
- Peter Goldsborough
- Jure Leskovec
- Sergey Levine
- Anshul B Kundaje
In Media Technology
- Shantanu Singh
- Juan C. Caicedo
- Nick Pawlowski
- Chelsea Finn
- Peter Goldsborough
- Percy Liang
- Jure Leskovec
- Anne E Carpenter
In Molecular Biology
- Percy Liang
- Juan C. Caicedo
- Chelsea Finn
- Anne E Carpenter
- Shantanu Singh
- Jure Leskovec
- Michihiro Yasunaga
- Sergey Levine
Citations in the corpus
- CytoGAN: Generative Modeling of Cell Images (2017, background): “[3] recently outlined the state and challenges of the morphological profiling problem.”
- WILDS: A Benchmark of in-the-Wild Distribution Shifts (2020, positive): “These batch effects make it difficult to draw conclusions from data across experimental batches (Leek et al., 2010; Parker & Leek, 2012; Soneson et al., 2014; Nygaard et al., 2016; Caicedo et al., 2017).”