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Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets

Mass cytometry (CyTOF) is a technology that has revolutionised single-cell biology. By detecting over 40 proteins on millions of single cells, CyTOF allows the characterisation of cell subpopulations in unprecedented detail. However, most CyTOF studies require the integration of data from multiple C...

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Autores principales: Trussart, Marie, Teh, Charis E, Tan, Tania, Leong, Lawrence, Gray, Daniel HD, Speed, Terence P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500954/
https://www.ncbi.nlm.nih.gov/pubmed/32894218
http://dx.doi.org/10.7554/eLife.59630
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author Trussart, Marie
Teh, Charis E
Tan, Tania
Leong, Lawrence
Gray, Daniel HD
Speed, Terence P
author_facet Trussart, Marie
Teh, Charis E
Tan, Tania
Leong, Lawrence
Gray, Daniel HD
Speed, Terence P
author_sort Trussart, Marie
collection PubMed
description Mass cytometry (CyTOF) is a technology that has revolutionised single-cell biology. By detecting over 40 proteins on millions of single cells, CyTOF allows the characterisation of cell subpopulations in unprecedented detail. However, most CyTOF studies require the integration of data from multiple CyTOF batches usually acquired on different days and possibly at different sites. To date, the integration of CyTOF datasets remains a challenge due to technical differences arising in multiple batches. To overcome this limitation, we developed an approach called CytofRUV for analysing multiple CyTOF batches, which includes an R-Shiny application with diagnostic plots. CytofRUV can correct for batch effects and integrate data from large numbers of patients and conditions across batches, to confidently compare cellular changes and correlate these with clinically relevant outcomes.
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spelling pubmed-75009542020-09-21 Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets Trussart, Marie Teh, Charis E Tan, Tania Leong, Lawrence Gray, Daniel HD Speed, Terence P eLife Computational and Systems Biology Mass cytometry (CyTOF) is a technology that has revolutionised single-cell biology. By detecting over 40 proteins on millions of single cells, CyTOF allows the characterisation of cell subpopulations in unprecedented detail. However, most CyTOF studies require the integration of data from multiple CyTOF batches usually acquired on different days and possibly at different sites. To date, the integration of CyTOF datasets remains a challenge due to technical differences arising in multiple batches. To overcome this limitation, we developed an approach called CytofRUV for analysing multiple CyTOF batches, which includes an R-Shiny application with diagnostic plots. CytofRUV can correct for batch effects and integrate data from large numbers of patients and conditions across batches, to confidently compare cellular changes and correlate these with clinically relevant outcomes. eLife Sciences Publications, Ltd 2020-09-07 /pmc/articles/PMC7500954/ /pubmed/32894218 http://dx.doi.org/10.7554/eLife.59630 Text en © 2020, Trussart et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Trussart, Marie
Teh, Charis E
Tan, Tania
Leong, Lawrence
Gray, Daniel HD
Speed, Terence P
Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets
title Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets
title_full Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets
title_fullStr Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets
title_full_unstemmed Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets
title_short Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets
title_sort removing unwanted variation with cytofruv to integrate multiple cytof datasets
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500954/
https://www.ncbi.nlm.nih.gov/pubmed/32894218
http://dx.doi.org/10.7554/eLife.59630
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