The application of metagenomic next-generation sequencing in pathogen diagnosis: a bibliometric analysis based on Web of Science
Sike He, Jingwen Wei, Jiaming Feng, Dan Liu, Neng Wang, Li‐Yu Chen, Ying Xiong
Abstract
Background: Infectious disease is a large burden on public health globally. Metagenomic next-generation sequencing (mNGS) has become popular as a new tool for pathogen diagnosis with numerous advantages compared to conventional methods. Recently, research on mNGS increases yearly. However, no bibliometric analysis has systematically presented the full spectrum of this research field. Therefore, we reviewed all the publications associated with this topic and performed this study to analyze the comprehensive status and future hotspots of mNGS for infectious disease diagnosis. Methods: The literature was searched in the Web of Science Core Collection and screened without year or language restrictions, and the characteristics of the studies were also identified. The outcomes included publication years, study types, journals, countries, authorship, institutions, frontiers, and hotspots with trends. Statistical analysis and visualization were conducted using VOSviewer (version 1.6.16) and CiteSpace (version 6.1. R3). Results: were the most commonly cited and co-cited journals. Institutions and researchers from China contributed the most to this field, followed by those from the USA. The hotspots and frontiers of these studies are pneumonia, tuberculosis, and central nervous system infections. Conclusion: This study determined that mNGS is a hot topic in the diagnosis of infectious diseases with development trends and provides insights into researchers, institutions, hotspots and frontiers in mNGS, which can offer references to related researchers and future research.