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 journalArticleResearchpeer-review

8 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 languageEnglish
Pages (from-to)4187-4189
Number of pages3
JournalBioinformatics
Volume35
Issue number20
DOIs
Publication statusPublished - 15 Oct 2019
Externally publishedYes

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