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scDiffCoAM: A complete framework to identify potential biomarkers for esophageal squamous cell carcinoma using
Manaswita Saikia1, Dhruba K Bhattacharyya, Jugal K Kalita
1Department of Computer Science and Engineering, Tezpur University, Napaam, Tezpur 784028, Assam, India.
Journal of Biosciences
|August 9, 2024
Summary
This study introduces scDiffCoAM, a novel framework for analyzing sparse single-cell RNA sequencing data to identify gene network modules and potential biomarkers in diseases like esophageal squamous cell carcinoma.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Single-cell RNA sequencing (scRNA-Seq) offers insights into cellular processes and gene interactions.
- Data scarcity in scRNA-Seq presents significant analytical challenges.
Purpose of the Study:
- To develop a robust differential co-expression (DCE) analysis framework for scRNA-Seq data.
- To identify network modules and potential hub-genes (biomarkers) from sparse scRNA-Seq datasets.
Main Methods:
- Proposed a complete differential co-expression (DCE) analysis framework named scDiffCoAM.
- Validated the framework using an scRNA-Seq dataset from esophageal squamous cell carcinoma (ESCC).
- Compared scDiffCoAM against four existing hub-gene identification methods.
Main Results:
- The scDiffCoAM framework demonstrated satisfactory performance on the ESCC dataset.
- scDiffCoAM outperformed existing methods in identifying unique potential biomarkers.
- Identified biomarkers were validated both statistically and biologically.
Conclusions:
- scDiffCoAM is an effective method for analyzing sparse scRNA-Seq data.
- The framework successfully identifies novel potential biomarkers for diseases.
- This approach enhances the understanding of gene-gene interactions in cellular heterogeneity.
