A set-theoretic definition of cell types with an algebraic structure on gene regulatory networks and application in annotation of RNA-seq data.

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Tytuł:: A set-theoretic definition of cell types with an algebraic structure on gene regulatory networks and application in annotation of RNA-seq data.
Autorzy:: Okano Y; Department of Physiology, Keio University School of Medicine, 35, Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.
Kase Y; Department of Physiology, Keio University School of Medicine, 35, Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.
Okano H; Department of Physiology, Keio University School of Medicine, 35, Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan. Electronic address: .
Źródło:: Stem cell reports [Stem Cell Reports] 2023 Jan 10; Vol. 18 (1), pp. 113-130. Date of Electronic Publication: 2022 Nov 17.
Typ publikacji:: Journal Article; Research Support, Non-U.S. Gov't
Język:: English
Imprint Name(s):: Original Publication: [Cambridge, MA] : Cell Press, c 2013-
MeSH Terms:: RNA*/genetics
Gene Regulatory Networks*
RNA-Seq ; Sequence Analysis, RNA/methods ; Single-Cell Analysis/methods ; Gene Expression Profiling/methods
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Contributed Indexing:: Keywords: annotation; cell type; cellular state; mathematical model; scRNA-seq; set theory; transcriptome
Substance Nomenclature:: 63231-63-0 (RNA)
Entry Date(s):: Date Created: 20221118 Date Completed: 20230113 Latest Revision: 20230210
Update Code:: 20240104
PubMed Central ID:: PMC9859932
DOI:: 10.1016/j.stemcr.2022.10.015
PMID:: 36400029
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The emergence of single-cell RNA sequencing (RNA-seq) has radically changed the observation of cellular diversity. Although annotations of RNA-seq data require preserved properties among cells of an identity, annotations using conventional methods have not been able to capture universal characters of a cell type. Analysis of expression levels cannot be accurately annotated for cells because differences in transcription do not necessarily explain biological characteristics in terms of cellular functions and because the data themselves do not inform about the correct mapping between cell types and genes. Hence, in this study, we developed a new representation of cellular identities that can be compared over different datasets while preserving nontrivial biological semantics. To generalize the notion of cell types, we developed a new framework to manage cellular identities in terms of set theory. We provided further insights into cells by installing mathematical descriptions of cell biology. We also performed experiments that could correspond to practical applications in annotations of RNA-seq data.
Competing Interests: Conflict of interests H.O. is a compensated scientific consultant for San Bio Co., Ltd.; RMiC; and K Pharma, Inc.
(Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

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