Differential expression and KEGG GSEA analysis of NEQC-normalized Illumina microarray data comparing E. coli infection vs mock samples, using limma and clusterProfiler.
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Updated
Aug 9, 2026 - R
Differential expression and KEGG GSEA analysis of NEQC-normalized Illumina microarray data comparing E. coli infection vs mock samples, using limma and clusterProfiler.
Computational analysis of multiple myeloma progression — 7-method cross-validation (DEG, GSEA, ML, deep learning, clustering) on 859 patients achieving 93.8% classification accuracy
Code for integrating transcriptomics, methylation, and proteomics data using DIABLO
RNA-seq time course analysis pipeline: DESeq2 → GSEA → Pathview → interactive HTML report
A version of Single Sample GSEA adapted to the sparsity of single cell RNA-seq data
Reproducible Nextflow DSL2 pipeline for gene set enrichment analysis using DESeq2, fgsea, Docker, and publication-quality visualization.
Gene expression analysis to identify biomarkers for early lung cancer detection (SCLC & NSCLC)
The Tasmanian devil is endangered due to Devil Facial Tumour Disease (DFTD), a contagious cancer with no current treatment. Previous study has investigated the anticancer properties of Tasmanian devil cathelicidins. This report intends to reproduce the enrichment analysis results of the study and further analyze their data.
R-based machine learning workflows for cancer transcriptomics, including random forest classification, feature selection, molecular clustering and pathway analysis.
DNA damage and repair transcriptomics integrating DESeq2, race/disease contrasts, metabolism/immunology panels, ashr shrinkage, and GO/KEGG/Reactome enrichment
Downstream Analysis of RNA-Seq Results in R: GSEA, PPI Networks, and Biological Interpretation
Reproducible R/Bioconductor GSEA analysis of immune activation signatures linked to DNA origami nanostructure design.
DGE and GSEA analysis of TB biomarkers from cfRNA-seq data
Investigating the transcriptomic architecture and functional landscape of NAA15-associated Neurodevelopmental Disorders (NDD) through comparative gene expression profiling.
ggg is a cutting-edge development framework designed for ultra-fast data processing and analysis. With advanced features and a user-friendly interface, ggg empowers developers to create efficient and robust applications for a wide range of industries.
Reproducible omics pipelines: AD brain snRNA-seq pseudobulk DE (GSE129308) · PyTorch cell-type classifier (donor-level split, acc 0.997) · 5XFAD ferroptosis RNA-seq + GSEA · citation auditor · GEO download tools · gut microbiome | 可复现生信项目集(兰州大学)
RNA-seq differential expression and functional enrichment analysis of GSE341745 using R and edgeR
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