Analysis code for the spectral flow cytometry pipeline published in The Journal of Immunology (2024). Superseded for general use by CAFÉ.
Interactive scRNA-seq UMAP visualization and biomarker discovery platform (Public Demo)
This is a pipeline for ingestion, cleaning, and spatial analysis of Akoya PCF images
Deep Graph Clustering for Transcriptomics analysis
End-to-end single-cell RNA-seq analysis pipeline in Python using a real public 10x Genomics dataset, including QC, clustering, marker gene analysis, annotation, and visualization.
Knowledge-driven computational framework that leverages large language model (LLM) embeddings to map the spatiotemporal functional organization of mouse embryonic development from spatial transcriptomics data.
Integrated analysis of normal, ER+, HER2+, TNBC and metastatic breast cancer single-cell transcriptomes to identify cell populations, epithelial tumor states and subtype-specific programs.
End-to-end spatial transcriptomics pipeline for 10x Genomics Visium human brain glioblastoma — cell type annotation, GBM subtype characterization, and spatial neighborhood analysis
Single-cell RNA-seq analysis workflow (Seurat + Scanpy). QC → HVG → PCA → UMAP → Leiden → marker annotation. POC: 10x PBMC 3k — 2,643 cells post-QC, 7 Leiden clusters mapped to canonical T/B/Monocyte/NK lineages.
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