MuPETFlow: multiple ploidy estimation tool from flow cytometry data

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Publicado en:BMC Genomics vol. 26 (2025), p. 1
Autor principal: Gómez-Muñoz, C
Otros Autores: Fischer, G
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Springer Nature B.V.
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Acceso en línea:Citation/Abstract
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024 7 |a 10.1186/s12864-025-11470-8  |2 doi 
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100 1 |a Gómez-Muñoz, C 
245 1 |a MuPETFlow: multiple ploidy estimation tool from flow cytometry data 
260 |b Springer Nature B.V.  |c 2025 
513 |a Journal Article 
520 3 |a BackgroundPloidy, representing the number of homologous chromosome sets, can be estimated from flow cytometry data acquired on cells stained with a fluorescent DNA dye. This estimation relies on a combination of tools that often require scripting, individual sample curation, and additional analyses.ResultsTo automate the ploidy estimation for multiple flow cytometry files, we developed MuPETFlow—a Shiny graphical user interface tool. MuPETFlow allows users to visualize cell fluorescence histograms, detect the peaks corresponding to the different cell cycle phases, perform a linear regression using standards, make ploidy or genome size predictions, and export results as figures and table files. The tool was benchmarked with known ploidy datasets from yeast and plant species, yielding consistent ploidy results. MuPETFlow's peaks detection and performance were also compared to those of other tools.ConclusionsMuPETFlow stands out as the only tool offering in-app ploidy detection, multiple peak detection, multi-sample visualization, and automation capabilities. These features significantly accelerate the analysis, making it especially valuable for projects involving large datasets. 
651 4 |a United States--US 
653 |a Standards 
653 |a Datasets 
653 |a Data acquisition 
653 |a Regression analysis 
653 |a Histograms 
653 |a Ploidy 
653 |a Open source software 
653 |a Data analysis 
653 |a Graphical user interface 
653 |a Genomes 
653 |a Flow cytometry 
653 |a Automation 
653 |a Yeast 
653 |a Plant species 
653 |a Python 
653 |a Cell cycle 
653 |a User interface 
653 |a Fluorescence 
653 |a Environmental 
700 1 |a Fischer, G 
773 0 |t BMC Genomics  |g vol. 26 (2025), p. 1 
786 0 |d ProQuest  |t Health & Medical Collection 
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