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Protocol for identification and computational analysis of human natural killer cells using flow cytometry and R

Identifying differential protein expression is routinely used to delineate natural killer (NK) cells from various sample cohorts. This protocol describes key steps for NK cell analysis: identifying human NK cells using flow gating, data export from FlowJo, data loading in R, dimensionality reduction...

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Detalles Bibliográficos
Autores principales: Kroll, Kyle, Reeves, R. Keith
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871333/
https://www.ncbi.nlm.nih.gov/pubmed/36853664
http://dx.doi.org/10.1016/j.xpro.2023.102044
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author Kroll, Kyle
Reeves, R. Keith
author_facet Kroll, Kyle
Reeves, R. Keith
author_sort Kroll, Kyle
collection PubMed
description Identifying differential protein expression is routinely used to delineate natural killer (NK) cells from various sample cohorts. This protocol describes key steps for NK cell analysis: identifying human NK cells using flow gating, data export from FlowJo, data loading in R, dimensionality reduction and visualization with Uniform Manifold Approximation and Projection, and generalized linear modeling with CyotGLMM. These analyses can help generate potential biomarkers of interest to identify NK cells across aging, treatment groups, and others. For complete details on the use and execution of this protocol, please refer to Kroll et al. (2022).(1)
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spelling pubmed-98713332023-01-25 Protocol for identification and computational analysis of human natural killer cells using flow cytometry and R Kroll, Kyle Reeves, R. Keith STAR Protoc Protocol Identifying differential protein expression is routinely used to delineate natural killer (NK) cells from various sample cohorts. This protocol describes key steps for NK cell analysis: identifying human NK cells using flow gating, data export from FlowJo, data loading in R, dimensionality reduction and visualization with Uniform Manifold Approximation and Projection, and generalized linear modeling with CyotGLMM. These analyses can help generate potential biomarkers of interest to identify NK cells across aging, treatment groups, and others. For complete details on the use and execution of this protocol, please refer to Kroll et al. (2022).(1) Elsevier 2023-01-19 /pmc/articles/PMC9871333/ /pubmed/36853664 http://dx.doi.org/10.1016/j.xpro.2023.102044 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Kroll, Kyle
Reeves, R. Keith
Protocol for identification and computational analysis of human natural killer cells using flow cytometry and R
title Protocol for identification and computational analysis of human natural killer cells using flow cytometry and R
title_full Protocol for identification and computational analysis of human natural killer cells using flow cytometry and R
title_fullStr Protocol for identification and computational analysis of human natural killer cells using flow cytometry and R
title_full_unstemmed Protocol for identification and computational analysis of human natural killer cells using flow cytometry and R
title_short Protocol for identification and computational analysis of human natural killer cells using flow cytometry and R
title_sort protocol for identification and computational analysis of human natural killer cells using flow cytometry and r
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871333/
https://www.ncbi.nlm.nih.gov/pubmed/36853664
http://dx.doi.org/10.1016/j.xpro.2023.102044
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