Automated analysis of bacterial flow cytometry data with FlowGateNIST.

Flow cytometry is commonly used to evaluate the performance of engineered bacteria. With increasing use of high-throughput experimental methods, there is a need for automated analysis methods for flow cytometry data. Here, we describe FlowGateNIST, a Python package for automated analysis of bacteria...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autor principal:	David Ross
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a7cc45b26240469a83bde873e76bb014
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:a7cc45b26240469a83bde873e76bb014
record_format	dspace
spelling	oai:doaj.org-article:a7cc45b26240469a83bde873e76bb0142021-12-02T20:17:53ZAutomated analysis of bacterial flow cytometry data with FlowGateNIST.1932-620310.1371/journal.pone.0250753https://doaj.org/article/a7cc45b26240469a83bde873e76bb0142021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0250753https://doaj.org/toc/1932-6203Flow cytometry is commonly used to evaluate the performance of engineered bacteria. With increasing use of high-throughput experimental methods, there is a need for automated analysis methods for flow cytometry data. Here, we describe FlowGateNIST, a Python package for automated analysis of bacterial flow cytometry data. The main components of FlowGateNIST perform automatic gating to differentiate between cells and background events and then between singlet and multiplet events. FlowGateNIST also includes a method for automatic calibration of fluorescence signals using fluorescence calibration beads. FlowGateNIST is open source and freely available with tutorials and example data to facilitate adoption by users with minimal programming experience.David RossPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0250753 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q David Ross Automated analysis of bacterial flow cytometry data with FlowGateNIST.
description	Flow cytometry is commonly used to evaluate the performance of engineered bacteria. With increasing use of high-throughput experimental methods, there is a need for automated analysis methods for flow cytometry data. Here, we describe FlowGateNIST, a Python package for automated analysis of bacterial flow cytometry data. The main components of FlowGateNIST perform automatic gating to differentiate between cells and background events and then between singlet and multiplet events. FlowGateNIST also includes a method for automatic calibration of fluorescence signals using fluorescence calibration beads. FlowGateNIST is open source and freely available with tutorials and example data to facilitate adoption by users with minimal programming experience.
format	article
author	David Ross
author_facet	David Ross
author_sort	David Ross
title	Automated analysis of bacterial flow cytometry data with FlowGateNIST.
title_short	Automated analysis of bacterial flow cytometry data with FlowGateNIST.
title_full	Automated analysis of bacterial flow cytometry data with FlowGateNIST.
title_fullStr	Automated analysis of bacterial flow cytometry data with FlowGateNIST.
title_full_unstemmed	Automated analysis of bacterial flow cytometry data with FlowGateNIST.
title_sort	automated analysis of bacterial flow cytometry data with flowgatenist.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/a7cc45b26240469a83bde873e76bb014
work_keys_str_mv	AT davidross automatedanalysisofbacterialflowcytometrydatawithflowgatenist
_version_	1718374364862218240

Automated analysis of bacterial flow cytometry data with FlowGateNIST.

Ejemplares similares