Data-analysis strategies for image-based cell profiling

Caicedo, Juan C.; Cooper, Sam; Heigwer, Florian; Warchal, Scott J.; Qiu, Peng; Molnár, Csaba; Vasilevich, Aliaksei; Barry, Joseph D.; Bansal, Harmanjit Singh; Kraus, Oren; Wawer, Mathias; Paavolainen, Lassi; Herrmann, Markus D.; Rohban, Mohammad Hossein; Hung, Jia‐Jang; Hennig, Holger; Concannon, John; Smith, Ian C. P.; Clemons, Paul A.; Singh, Shantanu; Rees, Paul; Horváth, Péter; Linington, Roger G.; Carpenter, Anne E.

doi:10.1038/nmeth.4397

Cited by 620 publications

(615 citation statements)

References 139 publications

(183 reference statements)

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“…Extended sets of image‐derived phenotypes can further be exploited for high‐dimensional cellular image analysis. More importantly, to support real‐time, continuous operation in FACED imaging flow cytometry at high‐throughput, it is essential to further integrate the system with the massively parallel data acquisition and processing platform, which could be realized by the use of graphic processing unit and/or field programmable gated array (FPGA). Not only can this integration accelerate image processing of numerous cell images, but also allows deep data analytics based on the aforementioned image‐derived phenotypes or deep machine‐learning‐based classification in real‐time.…”

Section: Resultsmentioning

confidence: 99%

A high‐throughput all‐optical laser‐scanning imaging flow cytometer with biomolecular specificity and subcellular resolution

Yan

Wong

et al. 2018

Journal of Biophotonics

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Image-based cellular assay advances approaches to dissect complex cellular characteristics through direct visualization of cellular functional structures. However, available technologies face a common challenge, especially when it comes to the unmet need for unraveling population heterogeneity at single-cell precision: higher imaging resolution (and thus content) comes at the expense of lower throughput, or vice versa. To overcome this challenge, a new type of imaging flow cytometer based upon an all-optical ultrafast laser-scanning imaging technique, called free-space angular-chirp-enhanced delay (FACED) is reported. It enables an imaging throughput (>20 000 cells s ) 1 to 2 orders of magnitude higher than the camera-based imaging flow cytometers. It also has 2 critical advantages over optical time-stretch imaging flow cytometry, which achieves a similar throughput: (1) it is widely compatible to the repertoire of biochemical contrast agents, favoring biomolecular-specific cellular assay and (2) it enables high-throughput visualization of functional morphology of individual cells with subcellular resolution. These capabilities enable multiparametric single-cell image analysis which reveals cellular heterogeneity, for example, in the cell-death processes demonstrated in this work-the information generally masked in non-imaging flow cytometry. Therefore, this platform empowers not only efficient large-scale single-cell measurements, but also detailed mechanistic analysis of complex cellular processes.

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Section: Resultsmentioning

confidence: 99%

A high‐throughput all‐optical laser‐scanning imaging flow cytometer with biomolecular specificity and subcellular resolution

Yan

Wong

et al. 2018

Journal of Biophotonics

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“…The application to chemically complex NPs of agnostic (or non-targeted) in vitro assays 69 combining cutting-edge computational approaches, optimized mass spectrometric (MS) data collection and analysis to elucidate chemical composition, and cytological profiling 70,71 now enables the generation of strong and specific hypotheses regarding bioactive NP components and the mechanisms through which they affect gene expression or cell phenotype. The application to chemically complex NPs of agnostic (or non-targeted) in vitro assays 69 combining cutting-edge computational approaches, optimized mass spectrometric (MS) data collection and analysis to elucidate chemical composition, and cytological profiling 70,71 now enables the generation of strong and specific hypotheses regarding bioactive NP components and the mechanisms through which they affect gene expression or cell phenotype.…”

Section: In Vitro Modelsmentioning

confidence: 99%

Improving natural product research translation: From source to clinical trial

et al. 2019

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While great interest in health effects of natural product (NP) including dietary supplements and foods persists, promising preclinical NP research is not consistently translating into actionable clinical trial (CT) outcomes. Generally considered the gold standard for assessing safety and efficacy, CTs, especially phase III CTs, are costly and require rigorous planning to optimize the value of the information obtained. More effective bridging from NP research to CT was the goal of a Septe mber, 2018 trans disci plina ry workshop. Participants emphasized that replicability and likelihood of successful translation depend on rigor in experimental design, interpretation, and reporting across the continuum of NP research. Discussions spanned good practices for NP characterization and quality control; use and interpretation of models (computational through in vivo) with strong clinical predictive validity; controls for experimental artefacts, especially for in vitro interrogation of bioactivity and mechanisms of action; rigorous assessment and interpretation of prior research; transparency in all reporting; and prioritization of research questions. Natural product clinical trials prioritized based on rigorous, convergent supporting data and current public health needs are most likely to be informative and ultimately affect public health. Thoughtful, coordinated implementation of these practices should enhance the knowledge gained from future NP research. K E Y W O R D S clinical predictive validity, dietary supplements, model systems, rigor and replicability, value of information | 43 SORKIN et al.still provide invaluable guidance, the results of such trials are often met with concerns that different design choiceswhether of product, dose, timing, participant eligibility criteria, outcomes, etc.-might have yielded a substantially different result. Each interventional trial represents a substantial investment, with well-powered Phase III CTs typically consuming more than $10 million and many person-years. 9,10 Additionally, as time and funds are limited, and participant pools may also be constrained, a decision to invest in a CT often precludes pursuing other research questions, 11 which may provide more useful public health-relevant knowledge than an RCT with an insufficient evidence base.

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“…Potential field imaging biases were estimated and removed by using a multi-image regression algorithm similar as previously done (Caicedo et al, 2017). Briefly, for each gene, the imaging bias at each binned location was estimated by averaging the normalized gene expression levels over 8 neighboring bins within each field followed by averaging across all fields.…”

Section: Seqfish Data Normalization and Bias Correctionmentioning

confidence: 99%

Decomposing spatially dependent and cell type specific contributions to cellular heterogeneity

Zhu

Shah

Dries

et al. 2018

Preprint

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Both the intrinsic regulatory network and spatial environment are contributors of cellular identity and result in cell state variations. However, their individual contributions remain poorly understood. Here we present a systematic approach to integrate both sequencing-and imaging-based single-cell transcriptomic profiles, thereby combining whole-transcriptomic and spatial information from these assays. We applied this approach to dissect the cell-type and spatial domain associated heterogeneity within the mouse visual cortex region. Our analysis identified distinct spatially associated signatures within glutamatergic and astrocyte cell compartments, indicating strong interactions between cells and their surrounding environment. Using these signatures as a guide to analyze single cell RNAseq data, we identified previously unknown, but spatially associated subpopulations. As such, our integrated approach provides a powerful tool for dissecting the roles of intrinsic regulatory networks and spatial environment in the maintenance of cellular states.

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Data-analysis strategies for image-based cell profiling

Abstract: This Review covers the steps required to create high-quality image-based profiles from high-throughput microscopy images.

Cited by 620 publications

References 139 publications

A high‐throughput all‐optical laser‐scanning imaging flow cytometer with biomolecular specificity and subcellular resolution

A high‐throughput all‐optical laser‐scanning imaging flow cytometer with biomolecular specificity and subcellular resolution

Improving natural product research translation: From source to clinical trial

Decomposing spatially dependent and cell type specific contributions to cellular heterogeneity

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