Using the Sankey diagram to visualize article features on the topics of whole-exome sequencing (WES) and whole-genome sequencing (WGS) since 2012: Bibliometric analysis

Abstract

Background: Sequencing technologies, such as whole-exome sequencing (WES) and whole-genome sequencing (WGS), have been increasingly applied to medical research in recent years. Which countries, journals, and institutes (called entities) contributed most to the fields (WES/WGS) remains unknown. Temporal bar graphs (TBGs) are frequently used in trend analysis of publications. However, how to draw the TBG on the Sankey diagram is not well understood in bibliometrics. We thus aimed to investigate the evolution of article entities in the WES/WGS fields using publication-based TBGs and compare the individual research achievements (IRAs) among entities.Methods: A total of 3599 abstracts downloaded from icite analysis were matched to entities, including article identity numbers, citations, publication years, journals, affiliated countries/regions of origin, and medical subject headings (MeSH terms) in PubMed on March 12, 2022. The relative citation ratio (RCR) was extracted from icite analysis to compute the hT index (denoting the IRA, taking both publications and citations into account) for each entity in the years between 2012 and 2021. Three types of visualizations were applied to display the trends of publications (e.g., choropleth maps and the enhanced TBGs) and IRAs (e.g., the flowchart on the Sankey diagram) for article entities in WES/WGS. Results:We observed that the 3 countries (the US, China, and the UK) occupied most articles in the WES/WGS fields since 2012, the 3 entities (i.e., top 5 journals, research institutes, and MeSH terms) were demonstrated on the enhanced TBGs, the top 2 MeSH terms were genetics and methods in WES and WGS, and the IRAs of 6 article entities with their hT-indices were succinctly and simultaneously displayed on a single Sankey diagram that was never launched in bibliographical studies. Conclusion:The number of WES/WGS-related articles has dramatically increased since 2017. TBGs, particularly with hTs on the Sankey, are recommended for research on a topic (or in a discipline) to compare trends of publications and IRAs for entities in future bibliographical studies.

The model of descriptive, diagnostic, predictive, and prescriptive analytics on 100 top-cited articles of nasopharyngeal carcinoma from 2013 to 2022: Bibliometric analysis

“…Three visual representations were used to display the relationship between variables using diagnostic analytics, including a network chart, [ 37 , 38 ] a chord diagram, [ 39 , 40 ] and a Sankey diagram. [ 14 , 41 , 42 ]…”

“…Three visual representations were used to display the relationship between variables using diagnostic analytics, including a network chart, [37,38] a chord diagram, [39,40] and a Sankey diagram. [14,41,42] Coword analysis [37,38] was performed to extract the chief keywords in clusters as themes (or leaders) represented by Keywords Plus that were retrieved from the WoSCC. The themes denoted by the chief keywords in clusters were assigned to T100NPC and countries using Equation 4.…”

A leading bibliometric author does not have a dominant contribution to research based on the CJAL score: Bibliometric analysis

“…A Sankey diagram [ 15 , 18 , 30 ] was used to display the CJAL scores for each article entity (document year, author cluster, WoS subject category, country of origin, author, research institute, and journal denoted by nodes) and their relationship (denoted by edge) evaluated by AAC.…”

Using coword analysis and chord diagrams to examine the effect of nutritional counseling and support (DCNS) on patients with oral and oropharyngeal cancer

“…Sankey diagrams were used to illustrate the relationship between variables. [30,31] The symbol of block was used to indicate proportional counts in variables. Edges were represented by a flow momentum from the left elements of variables to the adjacent right elements.…”