CytoBackBone: An algorithm for merging of phenotypic information from different cytometric profiles

Adrien Leite Pereira; Olivier Lambotte; Roger Le Grand; Antonio Cosma; Nicolas Tchitchek

doi:10.1093/bioinformatics/btz212

CytoBackBone: An algorithm for merging of phenotypic information from different cytometric profiles

Adrien Leite Pereira, Olivier Lambotte, Roger Le Grand, Antonio Cosma, Nicolas Tchitchek^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Research › peer-review

9 Citations (Scopus)

Abstract

Flow and mass cytometry are experimental techniques used to measure the level of proteins expressed by cells at the single-cell resolution. Several algorithms were developed in flow cytometry to increase the number of simultaneously measurable markers. These approaches aim to combine phenotypic information of different cytometric profiles obtained from different cytometry panels. Results: We present here a new algorithm, called CytoBackBone, which can merge phenotypic information from different cytometric profiles. This algorithm is based on nearest-neighbor imputation, but introduces the notion of acceptable and non-ambiguous nearest neighbors. We used mass cytometry data to illustrate the merging of cytometric profiles obtained by the CytoBackBone.

Original language	English
Pages (from-to)	4187-4189
Number of pages	3
Journal	Bioinformatics
Volume	35
Issue number	20
DOIs	https://doi.org/10.1093/bioinformatics/btz212
Publication status	Published - 15 Oct 2019
Externally published	Yes

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title = "CytoBackBone: An algorithm for merging of phenotypic information from different cytometric profiles",

abstract = "Flow and mass cytometry are experimental techniques used to measure the level of proteins expressed by cells at the single-cell resolution. Several algorithms were developed in flow cytometry to increase the number of simultaneously measurable markers. These approaches aim to combine phenotypic information of different cytometric profiles obtained from different cytometry panels. Results: We present here a new algorithm, called CytoBackBone, which can merge phenotypic information from different cytometric profiles. This algorithm is based on nearest-neighbor imputation, but introduces the notion of acceptable and non-ambiguous nearest neighbors. We used mass cytometry data to illustrate the merging of cytometric profiles obtained by the CytoBackBone.",

author = "Pereira, {Adrien Leite} and Olivier Lambotte and Grand, {Roger Le} and Antonio Cosma and Nicolas Tchitchek",

note = "Funding Information: This work was supported by the IDMIT infrastructure and funded by ANR Grant No. ANR-11-INBS-0008. Nicolas Tchitchek held fellowships from the ANRS (France Recherche Nord & Sud Sida-HIV H{\'e}patites). Publisher Copyright: {\textcopyright} 2019 The Author(s) 2019. Published by Oxford University Press.",

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AU - Pereira, Adrien Leite

AU - Lambotte, Olivier

AU - Grand, Roger Le

AU - Cosma, Antonio

AU - Tchitchek, Nicolas

N1 - Funding Information: This work was supported by the IDMIT infrastructure and funded by ANR Grant No. ANR-11-INBS-0008. Nicolas Tchitchek held fellowships from the ANRS (France Recherche Nord & Sud Sida-HIV Hépatites). Publisher Copyright: © 2019 The Author(s) 2019. Published by Oxford University Press.

PY - 2019/10/15

Y1 - 2019/10/15

N2 - Flow and mass cytometry are experimental techniques used to measure the level of proteins expressed by cells at the single-cell resolution. Several algorithms were developed in flow cytometry to increase the number of simultaneously measurable markers. These approaches aim to combine phenotypic information of different cytometric profiles obtained from different cytometry panels. Results: We present here a new algorithm, called CytoBackBone, which can merge phenotypic information from different cytometric profiles. This algorithm is based on nearest-neighbor imputation, but introduces the notion of acceptable and non-ambiguous nearest neighbors. We used mass cytometry data to illustrate the merging of cytometric profiles obtained by the CytoBackBone.

AB - Flow and mass cytometry are experimental techniques used to measure the level of proteins expressed by cells at the single-cell resolution. Several algorithms were developed in flow cytometry to increase the number of simultaneously measurable markers. These approaches aim to combine phenotypic information of different cytometric profiles obtained from different cytometry panels. Results: We present here a new algorithm, called CytoBackBone, which can merge phenotypic information from different cytometric profiles. This algorithm is based on nearest-neighbor imputation, but introduces the notion of acceptable and non-ambiguous nearest neighbors. We used mass cytometry data to illustrate the merging of cytometric profiles obtained by the CytoBackBone.

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CytoBackBone: An algorithm for merging of phenotypic information from different cytometric profiles

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