This repository contains the R code used for the analyses and figure generation reported in:
Pathway-Level Immune Signatures Associated with Sublingual Immunotherapy in Allergic Rhinitis
Christopher Wang
Montgomery Blair High School, USA
The National High School Journal of Science, 2026
Received: May 5, 2026
Accepted: July 30, 2026
Electronic access: September 30, 2026
This study investigates transcriptomic patterns associated with sublingual immunotherapy (SLIT) for allergic rhinitis using complementary bulk and single-cell RNA-sequencing datasets.
The analysis integrates:
- Bulk RNA-seq: GSE206149
- Single-cell RNA-seq: GSE200107
- Differential expression analysis
- Gene set enrichment analysis (GSEA)
- Patient-level pseudobulk differential expression
- Cell-type-specific pathway-level analysis
The central finding is that SLIT-associated transcriptomic differences are more apparent at the pathway level than at the level of individual genes.
The bulk RNA-seq dataset contains 255 samples and was used to compare transcriptional patterns between SLIT-treated and placebo samples.
Analyses included:
- DESeq2 normalization
- Differential expression analysis
- Gene ranking by log2 fold change
- Gene Ontology Biological Process enrichment using GSEA
Only a small number of genes showed large gene-level changes, while multiple immune-related pathways showed significant enrichment.
The single-cell dataset contains 15 expression libraries from 7 patients with paired pre- and post-treatment samples.
Major immune-cell populations analyzed included:
- CD4+ T cells
- CD8+ T cells
- B cells
- Monocytes
- Dendritic cells
- Natural killer cells
- Plasma cells
A patient-level pseudobulk framework was used to assess cell-type-specific transcriptional responses.
.
├── Step1_GSE206149_bulk_rnaseq_focused_v6.R
├── Step2_GSE200107_scRNA_SLIT_pre_post_v1.R
├── Step3_GSE200107_merged_restart_and_helper.R
├── Step4_gse_206149_gse_206152_validation.r
├── figures/
├── results/
├── metadata/
├── plots/
└── README.md