Single cell RNA Sequencing (scRNA-seq) Analysis of Pediatric Low Grade and High Grade Gliomas with Cell-type Annotation

Single-cell transcription analysis, particularly single-cell RNA sequencing (scRNA-seq), is a powerful technique that allows researchers to examine the gene expression of individual cells within a complex tissue. Instead of averaging gene expression across a bulk sample, this method provides a high-resolution view of cellular heterogeneity. This is exceptionally important for cancer research because tumors are not uniform masses; they consist of diverse cell populations, including cancer cells, immune cells, and stromal cells, each with unique transcriptional profiles. Understanding this cellular diversity is crucial for:  

• Identifying cancer subtypes: scRNA-seq can reveal previously unknown cancer cell subpopulations, leading to more precise tumor classification.  
• Deciphering tumor microenvironments: It allows researchers to map the interactions between cancer cells and their surrounding cells, which play a vital role in tumor growth and metastasis.  
• Understanding drug resistance: By analyzing gene expression changes in individual cells, researchers can identify mechanisms of drug resistance and develop more effective therapies.  
• Advancing immunotherapy: Single-cell analysis helps in characterizing immune cell populations within tumors, which is essential for developing and optimizing immunotherapies.

This project uses single cell RNA datasets from the Single-cell Pediatric Cancer Atlas Portal (SCPCA)

References

1. DeSisto, John et al., "Tumor and immune cell types interact to produce heterogeneous phenotypes of pediatric high-grade glioma" Neuro-Oncology, Volume 26, Issue 3, March 2024, Pages 538–552, https://doi.org/10.1093/neuonc/noad207
2. Cao, Yinghao et al., "SCSA: A Cell Type Annotation Tool for Single-Cell RNA-seq Data" Frontiers in Genetics, Volume 11 - 2020, May 2020, https://doi.org/10.3389/fgene.2020.00490
3. Complete single-cell RNAseq analysis walkthrough - Sanbomics (https://youtu.be/uvyG9yLuNSE?si=dVBqbTnWWGCYsK3E)
4. Transcriptomics Unveiled - An in-depth exploration of Single Cell RNASeq Analysis using Python - DigitalSreeni (https://youtu.be/IPePGXrSZHE?si=Bq-Qn7qQYudoS1FA)
5. Pediatric High Grade Glioma dataset - https://scpca.alexslemonade.org/projects/SCPCP000001
6. Pediatric Low Grade Glioma dataset - https://scpca.alexslemonade.org/projects/SCPCP000002