MuPETFlow: multiple ploidy estimation tool from flow cytometry data
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| Publicado en: | BMC Genomics vol. 26 (2025), p. 1 |
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Springer Nature B.V.
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| 022 | |a 1471-2164 | ||
| 024 | 7 | |a 10.1186/s12864-025-11470-8 |2 doi | |
| 035 | |a 3187547673 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 58495 |2 nlm | ||
| 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 | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3187547673/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3187547673/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3187547673/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |