Introduction

Oral inflammatory diseases, mainly caused by oral pathogens, represent local infections with the risk of developing into severe systemic conditions. Thus, precise early diagnosis and effective treatment are vital for safeguarding both oral and systemic health. Despite the availability of extensive oral inflammation datasets in public databases, researchers lacking programming expertise find it challenging to unlock their potential value due to insufficient analytical tools.

To address this issue, a team from China has developed the innovative online platform OralExplorer (Website: https://smuonco.shinyapps.io/OralExplorer/). The platform consolidates 35 datasets spanning six major disease types and includes 901 human oral inflammation samples, establishing a valuable tool for researching common oral diseases.

Fig.1 Data Processing and Analysis Modules of OralExplorer (Lin W., et al. 2024).

Overview of the OralExplorer Platform

Upon accessing the website's home page, users can immediately see the data analysis options available and the visual reference charts offered by the platform. This allows users to quickly grasp the website's capabilities and efficiently select the desired analysis module through the left-side navigation bar.

Differential Gene Analysis

Within the Differential Gene Analysis module, the developers identify genes with differential expression between disease and normal groups, sorted by log₂FoldChange values. Results are displayed in the form of a volcano plot, heatmap, and table. Users can tailor their analysis by selecting datasets, genes, p-value thresholds, log₂FoldChange thresholds, and preferred output formats. By clicking a button, they can instantly generate and download the relevant result visuals.

Immune Infiltration Analysis

Immune cell composition and proportions are crucial in the resolution of diseases. The OralExplorer database employs six sophisticated immune cell algorithms (TIMER, xCell, CIBERSORT, EPIC, quanTIseq, and MCPcounter) to assess the composition and proportion of immune cells in oral diseases, identifying differences in immune infiltration among groups. The results are visualized in heatmaps or box plots. Furthermore, this module explores associations between various immune cell infiltrations, including correlations between multiple immune cells, with scatter plots and bubble charts used for visualization.

Correlation Analysis

OralExplorer enables correlation analysis of single genes, multiple genes, gene-immune cell relationships, and gene-pathway interactions. Users can search specific disease types and gene sets, filter samples, and choose target genes, immune cells, or pathways. The platform provides Spearman and Pearson correlation analysis methods, as well as diverse visualization options including scatter plots, chord diagrams, and heatmaps.

Enrichment Analysis

The Enrichment Analysis module offers two commonly used pathway enrichment algorithms, GSEA and ssGSEA, along with 13,661 pathway gene sets from the MSigDB database. Users can choose from various visualization methods, such as bubble charts and GSEA enrichment plots, to display analysis results. Additionally, up to 15 pathways can be selected for visualization of ssGSEA enrichment analysis results in the form of a heatmap.

scRNA-seq Analysis

OralExplorer's scRNA-seq Analysis features visualization of single-cell analysis through cluster plots, feature plots, and heatmaps. Clustering analysis presents oral single-cell data post-dimensionality reduction, facilitating easy viewing of cell clustering outcomes. The ssGSEA scores for individual cells and clusters are calculated for visualization in feature plots and heatmaps. Users can choose genes or pathways of interest in feature plots to examine their expression in different cells, while heatmaps provide a clear view of gene and pathway expression across various clusters.

Conclusion

OralExplorer consolidates various oral inflammation datasets, providing an easy-to-use visualization interface and interactive features that allow dental researchers to explore oral disease data more efficiently. Additionally, the platform offers detailed analysis results and high-resolution images for convenient access and local download. As new datasets and analytical methods emerge, OralExplorer is likely to expand its application potential.