Bibliometric and visual analysis of single-cell sequencing from 2010 to 2022
Background: Single-cell sequencing (SCS) is a technique used to analyze the genome, transcriptome, epigenome, and other genetic data at the level of a single cell. The procedure is commonly utilized in multiple fields, including neurobiology, immunology, and microbiology, and has emerged as a key fo...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-01-01
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| Series: | Frontiers in Genetics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2023.1285599/full |
| _version_ | 1797357778213273600 |
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| author | Ling Chen Yantong Wan Tingting Yang Qi Zhang Qi Zhang Yuting Zeng Shuqi Zheng Shuqi Zheng Zhishan Ling Zhishan Ling Yupeng Xiao Yupeng Xiao Qingyi Wan Ruili Liu Chun Yang Guozhi Huang Guozhi Huang Qing Zeng Qing Zeng |
| author_facet | Ling Chen Yantong Wan Tingting Yang Qi Zhang Qi Zhang Yuting Zeng Shuqi Zheng Shuqi Zheng Zhishan Ling Zhishan Ling Yupeng Xiao Yupeng Xiao Qingyi Wan Ruili Liu Chun Yang Guozhi Huang Guozhi Huang Qing Zeng Qing Zeng |
| author_sort | Ling Chen |
| collection | DOAJ |
| description | Background: Single-cell sequencing (SCS) is a technique used to analyze the genome, transcriptome, epigenome, and other genetic data at the level of a single cell. The procedure is commonly utilized in multiple fields, including neurobiology, immunology, and microbiology, and has emerged as a key focus of life science research. However, a thorough and impartial analysis of the existing state and trends of SCS-related research is lacking. The current study aimed to map the development trends of studies on SCS during the years 2010–2022 through bibliometric software.Methods: Pertinent papers on SCS from 2010 to 2022 were obtained using the Web of Science Core Collection. Research categories, nations/institutions, authors/co-cited authors, journals/co-cited journals, co-cited references, and keywords were analyzed using VOSviewer, the R package “bibliometric”, and CiteSpace.Results: The bibliometric analysis included 9,929 papers published between 2010 and 2022, and showed a consistent increase in the quantity of papers each year. The United States was the source of the highest quantity of articles and citations in this field. The majority of articles were published in the periodical Nature Communications. Butler A was the most frequently quoted author on this topic, and his article “Integrating single-cell transcriptome data across diverse conditions, technologies, and species” has received numerous citations to date. The literature and keyword analysis showed that studies involving single-cell RNA sequencing (scRNA-seq) were prominent in this discipline during the study period.Conclusion: This study utilized bibliometric techniques to visualize research in SCS-related domains, which facilitated the identification of emerging patterns and future directions in the field. Current hot topics in SCS research include COVID-19, tumor microenvironment, scRNA-seq, and neuroscience. Our results are significant for scholars seeking to identify key issues and generate new research ideas. |
| first_indexed | 2024-03-08T14:50:04Z |
| format | Article |
| id | doaj.art-6e10bc69d4864bf2a07bd8ad7b58d716 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-03-08T14:50:04Z |
| publishDate | 2024-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-6e10bc69d4864bf2a07bd8ad7b58d7162024-01-11T04:28:14ZengFrontiers Media S.A.Frontiers in Genetics1664-80212024-01-011410.3389/fgene.2023.12855991285599Bibliometric and visual analysis of single-cell sequencing from 2010 to 2022Ling Chen0Yantong Wan1Tingting Yang2Qi Zhang3Qi Zhang4Yuting Zeng5Shuqi Zheng6Shuqi Zheng7Zhishan Ling8Zhishan Ling9Yupeng Xiao10Yupeng Xiao11Qingyi Wan12Ruili Liu13Chun Yang14Guozhi Huang15Guozhi Huang16Qing Zeng17Qing Zeng18Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaGuangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of BasicMedical Sciences, Southern Medical University, Guangzhou, ChinaSchool of Rehabilitation Medicine, Southern Medical University, Guangzhou, ChinaDepartment of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaSchool of Rehabilitation Medicine, Southern Medical University, Guangzhou, ChinaDepartment of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaDepartment of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaSchool of Rehabilitation Medicine, Southern Medical University, Guangzhou, ChinaDepartment of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaSchool of Rehabilitation Medicine, Southern Medical University, Guangzhou, ChinaDepartment of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaSchool of Rehabilitation Medicine, Southern Medical University, Guangzhou, ChinaSchool of Rehabilitation Medicine, Southern Medical University, Guangzhou, ChinaSchool of Rehabilitation Medicine, Southern Medical University, Guangzhou, ChinaDongguan Key Laboratory of Stem Cell and Regenerative Tissue Engineering, Guangdong Medical University, Dongguan, ChinaDepartment of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaSchool of Rehabilitation Medicine, Southern Medical University, Guangzhou, ChinaDepartment of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, ChinaSchool of Rehabilitation Medicine, Southern Medical University, Guangzhou, ChinaBackground: Single-cell sequencing (SCS) is a technique used to analyze the genome, transcriptome, epigenome, and other genetic data at the level of a single cell. The procedure is commonly utilized in multiple fields, including neurobiology, immunology, and microbiology, and has emerged as a key focus of life science research. However, a thorough and impartial analysis of the existing state and trends of SCS-related research is lacking. The current study aimed to map the development trends of studies on SCS during the years 2010–2022 through bibliometric software.Methods: Pertinent papers on SCS from 2010 to 2022 were obtained using the Web of Science Core Collection. Research categories, nations/institutions, authors/co-cited authors, journals/co-cited journals, co-cited references, and keywords were analyzed using VOSviewer, the R package “bibliometric”, and CiteSpace.Results: The bibliometric analysis included 9,929 papers published between 2010 and 2022, and showed a consistent increase in the quantity of papers each year. The United States was the source of the highest quantity of articles and citations in this field. The majority of articles were published in the periodical Nature Communications. Butler A was the most frequently quoted author on this topic, and his article “Integrating single-cell transcriptome data across diverse conditions, technologies, and species” has received numerous citations to date. The literature and keyword analysis showed that studies involving single-cell RNA sequencing (scRNA-seq) were prominent in this discipline during the study period.Conclusion: This study utilized bibliometric techniques to visualize research in SCS-related domains, which facilitated the identification of emerging patterns and future directions in the field. Current hot topics in SCS research include COVID-19, tumor microenvironment, scRNA-seq, and neuroscience. Our results are significant for scholars seeking to identify key issues and generate new research ideas.https://www.frontiersin.org/articles/10.3389/fgene.2023.1285599/fullsingle-cell sequencingVOSviewerCiteSpacevisual analysisbibliometric |
| spellingShingle | Ling Chen Yantong Wan Tingting Yang Qi Zhang Qi Zhang Yuting Zeng Shuqi Zheng Shuqi Zheng Zhishan Ling Zhishan Ling Yupeng Xiao Yupeng Xiao Qingyi Wan Ruili Liu Chun Yang Guozhi Huang Guozhi Huang Qing Zeng Qing Zeng Bibliometric and visual analysis of single-cell sequencing from 2010 to 2022 Frontiers in Genetics single-cell sequencing VOSviewer CiteSpace visual analysis bibliometric |
| title | Bibliometric and visual analysis of single-cell sequencing from 2010 to 2022 |
| title_full | Bibliometric and visual analysis of single-cell sequencing from 2010 to 2022 |
| title_fullStr | Bibliometric and visual analysis of single-cell sequencing from 2010 to 2022 |
| title_full_unstemmed | Bibliometric and visual analysis of single-cell sequencing from 2010 to 2022 |
| title_short | Bibliometric and visual analysis of single-cell sequencing from 2010 to 2022 |
| title_sort | bibliometric and visual analysis of single cell sequencing from 2010 to 2022 |
| topic | single-cell sequencing VOSviewer CiteSpace visual analysis bibliometric |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2023.1285599/full |
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