High-accuracy ML model for leukemic stem cell (LSC) identification from single-cell multi-omics data (TEA‑seq, CITE‑seq, scRNA‑seq).
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Updated
Jan 11, 2026 - Jupyter Notebook
High-accuracy ML model for leukemic stem cell (LSC) identification from single-cell multi-omics data (TEA‑seq, CITE‑seq, scRNA‑seq).
Single-Cell Atlas Builder is a modular platform for processing, integrating, and visualizing single-cell RNA-seq datasets. It combines FastAPI, Scanpy, and CellTypist for efficient analysis, with optional LLM-powered summaries for cluster and pathway interpretation.
End-to-end single-cell RNA-seq pipeline with scVI, Scanpy, and CellTypist for QC, clustering, annotation, and differential expression.
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