Complex Analysis of Single-Cell RNA Sequencing Data.

Autor: Khozyainova AA; Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia. khozyainova@onco.tnimc.ru., Valyaeva AA; Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, 119991, Russia.; Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, 119991, Russia., Arbatsky MS; Laboratory of Artificial Intelligence and Bioinformatics, The Russian Clinical Research Center for Gerontology, Pirogov Russian National Medical University, Moscow, 129226, Russia.; School of Public Administration, Lomonosov Moscow State University, Moscow, 119991, Russia.; Faculty of Fundamental Medicine, Lomonosov Moscow State University, Moscow, 119991, Russia., Isaev SV; Research Institute of Personalized Medicine, National Center for Personalized Medicine of Endocrine Diseases, National Medical Research Center for Endocrinology, Moscow, 117036, Russia., Iamshchikov PS; Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia.; Laboratory of Complex Analysis of Big Bioimage Data, National Research Tomsk State University, Tomsk, 634050, Russia., Volchkov EV; Department of Oncohematology, Dmitry Rogachev National Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, 117198, Russia., Sabirov MS; Laboratory of Bioinformatics and Molecular Genetics, Koltzov Institute of Developmental Biology of the Russian Academy of Sciences, Moscow, 119334, Russia., Zainullina VR; Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia., Chechekhin VI; Faculty of Fundamental Medicine, Lomonosov Moscow State University, Moscow, 119991, Russia., Vorobev RS; Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia., Menyailo ME; Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia., Tyurin-Kuzmin PA; Faculty of Fundamental Medicine, Lomonosov Moscow State University, Moscow, 119991, Russia., Denisov EV; Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia.
Jazyk: angličtina
Zdroj: Biochemistry. Biokhimiia [Biochemistry (Mosc)] 2023 Feb; Vol. 88 (2), pp. 231-252.
DOI: 10.1134/S0006297923020074
Abstrakt: Single-cell RNA sequencing (scRNA-seq) is a revolutionary tool for studying the physiology of normal and pathologically altered tissues. This approach provides information about molecular features (gene expression, mutations, chromatin accessibility, etc.) of cells, opens up the possibility to analyze the trajectories/phylogeny of cell differentiation and cell-cell interactions, and helps in discovery of new cell types and previously unexplored processes. From a clinical point of view, scRNA-seq facilitates deeper and more detailed analysis of molecular mechanisms of diseases and serves as a basis for the development of new preventive, diagnostic, and therapeutic strategies. The review describes different approaches to the analysis of scRNA-seq data, discusses the advantages and disadvantages of bioinformatics tools, provides recommendations and examples of their successful use, and suggests potential directions for improvement. We also emphasize the need for creating new protocols, including multiomics ones, for the preparation of DNA/RNA libraries of single cells with the purpose of more complete understanding of individual cells.
Databáze: MEDLINE
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