Content area

Abstract

Background

Ploidy, 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.

Results

To 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.

Conclusions

MuPETFlow 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.

Details

1009240
Business indexing term
Title
MuPETFlow: multiple ploidy estimation tool from flow cytometry data
Publication title
BMC Genomics; London
Volume
26
Pages
1-5
Publication year
2025
Publication date
2025
Section
Software
Publisher
Springer Nature B.V.
Place of publication
London
Country of publication
Netherlands
Publication subject
e-ISSN
14712164
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-03-26
Milestone dates
2024-09-09 (Received); 2025-03-11 (Accepted); 2025-03-26 (Published)
Publication history
 
 
   First posting date
26 Mar 2025
ProQuest document ID
3187547673
Document URL
https://www.proquest.com/scholarly-journals/mupetflow-multiple-ploidy-estimation-tool-flow/docview/3187547673/se-2?accountid=208611
Copyright
© 2025. This work is licensed under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-04-21
Database
ProQuest One Academic