holoviz/holoviews: Version 1.12.7

Rudiger, Philipp; Stevens, Jean-Luc; Bednar, James A.; Nijholt, Bas; Andrew, Andrew; Chris, B; Tenner, Vasco T.; Mease, Jon; Randelhoff, Achim; maxalbert,; Kaiser, Markus; gh, ea; stonebig,; jordansamuels,; henriqueribeiro,; Bampton, John; Lowe, Scott W.; Stephan, Daniel; arabidopsis,; Langer, Yuval; Barth, Lukas; Bois, Justin S.; Signell, J.; Lb, Florian; Lustig, Irv; Tolmie, Andrew; Klein, Almar; Portner, Benjamin W.; Monthe, Anthony; Yusifov, Anar

doi:10.5281/zenodo.3551257

2019

DOI: 10.5281/zenodo.3551257

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holoviz/holoviews: Version 1.12.7

Philipp Rudiger¹,

Jean-Luc Stevens²,

James A. Bednar³

et al.

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Toward reproducible, scalable, and robust data analysis across multiplex tissue imaging platforms

Burlingame

Eng

Thibault

et al. 2020

Preprint

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The emergence of megascale single-cell multiplex tissue imaging (MTI) datasets necessitates reproducible, scalable, and robust tools for cell phenotyping and spatial analysis. We developed open-source, graphics processing unit (GPU)-accelerated tools for intensity normalization, phenotyping, and microenvironment characterization. We deploy the toolkit on a human breast cancer (BC) tissue microarray stained by cyclic immunofluorescence and benchmark our cell phenotypes against a published MTI dataset. Finally, we demonstrate an integrative analysis revealing BC subtype-specific features.

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Toward reproducible, scalable, and robust data analysis across multiplex tissue imaging platforms

Burlingame

Eng

Thibault

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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holoviz/holoviews: Version 1.12.7

Cited by 1 publication

References 0 publications

Toward reproducible, scalable, and robust data analysis across multiplex tissue imaging platforms

Toward reproducible, scalable, and robust data analysis across multiplex tissue imaging platforms

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