PyPlaque is an open-source python package for phenotypic analysis of virus plaque assays

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Publicat a:Scientific Reports (Nature Publisher Group) vol. 15, no. 1 (2025), p. 36187-36205
Autor principal: De, Trina
Altres autors: Andriasyan, Vardan, Yakimovich, Artur
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Nature Publishing Group
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100 1 |a De, Trina  |u Center for Advanced Systems Understanding (CASUS), Görlitz, Germany (ROR: https://ror.org/042b69396) (GRID: grid.510908.5); Helmholtz-Zentrum Dresden-Rossendorf e. V. (HZDR), Dresden, Germany (ROR: https://ror.org/01zy2cs03) (GRID: grid.40602.30) (ISNI: 0000 0001 2158 0612) 
245 1 |a PyPlaque is an open-source python package for phenotypic analysis of virus plaque assays 
260 |b Nature Publishing Group  |c 2025 
513 |a Journal Article 
520 3 |a Virological plaque assays are the primary method for quantifying infectious particles in a suspension, achieved by incubating a serial dilution of the virus with a monolayer of indicator cells. Existing software tools for quantification of plaque assay images lack modularity, show measurements disagreement or are closed-source - a common hurdle in bioimage analysis. We introduce PyPlaque, an open-source Python package focusing on flexibility and modularity rather than a bulky graphic user interface. Unlike previous methods, an abstracted architecture using object-oriented programming allows accommodation of various experimental containers and specimen carriers as data structures while focusing on phenotype-specific information. Aligned with the logical flow of experimental design and desired quantifications, it delivers insights at multiple granularity levels, facilitating detailed analysis. We demonstrate how this approach allows to focus on alleviating the disagreement in measurements. Furthermore, similar design is generalisable to diverse datasets in various biological contexts that fit our structural paradigm. 
653 |a Object oriented programming 
653 |a Infections 
653 |a Plaque assay 
653 |a Pathogens 
653 |a Experimental design 
653 |a Open source software 
653 |a Experiments 
653 |a Phenotypes 
653 |a Microscopy 
653 |a Flexibility 
653 |a Data analysis 
653 |a Viruses 
653 |a Data science 
653 |a Python 
653 |a Environmental 
700 1 |a Andriasyan, Vardan  |u Department of Molecular Life Sciences, University of Zürich, Zürich, Switzerland (ROR: https://ror.org/02crff812) (GRID: grid.7400.3) (ISNI: 0000 0004 1937 0650); Institute of Computer Science, University of Wrocław, Wrocław, Poland (ROR: https://ror.org/00yae6e25) (GRID: grid.8505.8) (ISNI: 0000 0001 1010 5103) 
700 1 |a Yakimovich, Artur  |u Center for Advanced Systems Understanding (CASUS), Görlitz, Germany (ROR: https://ror.org/042b69396) (GRID: grid.510908.5); Helmholtz-Zentrum Dresden-Rossendorf e. V. (HZDR), Dresden, Germany (ROR: https://ror.org/01zy2cs03) (GRID: grid.40602.30) (ISNI: 0000 0001 2158 0612); Department of Molecular Life Sciences, University of Zürich, Zürich, Switzerland (ROR: https://ror.org/02crff812) (GRID: grid.7400.3) (ISNI: 0000 0004 1937 0650); Institute of Computer Science, University of Wrocław, Wrocław, Poland (ROR: https://ror.org/00yae6e25) (GRID: grid.8505.8) (ISNI: 0000 0001 1010 5103) 
773 0 |t Scientific Reports (Nature Publisher Group)  |g vol. 15, no. 1 (2025), p. 36187-36205 
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