Forskning
Udskriv Udskriv
Switch language
Region Hovedstaden - en del af Københavns Universitetshospital
Udgivet

Analysis of Mass Cytometry Data

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Harvard

APA

CBE

MLA

Vancouver

Author

Bibtex

@article{88ff5377fcfe4e2abb7417e38b66bdc1,
title = "Analysis of Mass Cytometry Data",
abstract = "The CyTOF system produces single cell protein expression data similar to that from flow cytometry, but with an increased number of features measured. Traditionally, analysis of these data is carried out using manual gating, but with the increased dimensionality, manual gating becomes a suboptimal analysis strategy in some cases. To address this, a number of data analysis tools for tasks such as clustering, differential abundance analysis, and visualization have been developed and made freely available. We here introduce some of the more popular tools for CyTOF analysis and exemplify their utility in a common analysis workflow.",
author = "Pedersen, {Christina B} and Olsen, {Lars R}",
year = "2019",
doi = "10.1007/978-1-4939-9454-0_17",
language = "English",
volume = "1989",
pages = "267--279",
journal = "Methods in Molecular Biology",
issn = "1064-3745",
publisher = "Humana Press, Inc",

}

RIS

TY - JOUR

T1 - Analysis of Mass Cytometry Data

AU - Pedersen, Christina B

AU - Olsen, Lars R

PY - 2019

Y1 - 2019

N2 - The CyTOF system produces single cell protein expression data similar to that from flow cytometry, but with an increased number of features measured. Traditionally, analysis of these data is carried out using manual gating, but with the increased dimensionality, manual gating becomes a suboptimal analysis strategy in some cases. To address this, a number of data analysis tools for tasks such as clustering, differential abundance analysis, and visualization have been developed and made freely available. We here introduce some of the more popular tools for CyTOF analysis and exemplify their utility in a common analysis workflow.

AB - The CyTOF system produces single cell protein expression data similar to that from flow cytometry, but with an increased number of features measured. Traditionally, analysis of these data is carried out using manual gating, but with the increased dimensionality, manual gating becomes a suboptimal analysis strategy in some cases. To address this, a number of data analysis tools for tasks such as clustering, differential abundance analysis, and visualization have been developed and made freely available. We here introduce some of the more popular tools for CyTOF analysis and exemplify their utility in a common analysis workflow.

U2 - 10.1007/978-1-4939-9454-0_17

DO - 10.1007/978-1-4939-9454-0_17

M3 - Journal article

VL - 1989

SP - 267

EP - 279

JO - Methods in Molecular Biology

JF - Methods in Molecular Biology

SN - 1064-3745

ER -

ID: 59011337