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2023_FLC_snRNA_Khasayer

End-to-end snRNA-seq analysis of fibrolamellar carcinoma (FLC) tumor samples — includes QC, Harmony batch integration, and CellChat cell-cell communication analysis

Overview

Fibrolamellar carcinoma (FLC) is a rare primary liver cancer affecting adolescents and young adults. This project applies single-nucleus RNA-seq to characterize the cellular composition and communication landscape of FLC tumors, with the goal of identifying disease-relevant cell populations and rewired signaling pathways.

Analysis pipeline

The analysis is organized as a series of R Markdown (.Rmd) documents, designed to be run sequentially:

Step Description
1. QC Ambient RNA removal, doublet detection, per-sample quality filtering
2. Clustering Dimensionality reduction (PCA, UMAP), graph-based clustering
3. Cell type identification Marker-based annotation of cell populations
4. Harmony integration Batch correction and cross-sample integration using Harmony
5. CellChat analysis Inference of cell-cell communication networks and signaling pathways

Data

  • Input: Raw count matrices from 10x Chromium single-nucleus RNA-seq
  • Samples: FLC tumor samples (Khashayar lab cohort)

Dependencies

Related publication

Farghli, A. R., Chan, M., Sherman, M. S., et al. (2024). Single-cell multi-omic analysis of fibrolamellar carcinoma reveals rewired cell-to-cell communication patterns and unique vulnerabilities. bioRxiv.

Contact

Alaa R. Farghli — LinkedIn | Google Scholar | ORCID

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Single-nucleus RNA-seq analysis of FLC samples generated by the Khashayar lab, including QC, harmony integration, and CellChat analysis

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