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A hands-on single-cell RNA-seq bone marrow project focused on learning the full reasoning chain: how raw expression matrices become QC-filtered cells, clusters, immune-cell annotations, marker evidence, pathway scores, and biologically interpretable results.
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.
This repository contains code to analyze single-nuclei RNA sequencing data from the ventrobasal thalamus and principal sensory trigeminal nucleus in neonatal mice. It performs quality control, clustering, and identification of marker genes to characterize cell types and their interconnectivity during early whisker pathway development.
Single-cell RNA-seq analysis of periodontitis PBMC samples using Seurat. Performed quality control, dimensionality reduction (PCA, UMAP), clustering, marker gene identification, and immune cell annotation to characterize cellular heterogeneity in GSE174609.