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Updated: Mar 15, 2026
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Published on: July 3, 2025
scan_tcga tools for integrated epigenomic and transcriptomic analysis of tumor subgroups
Aniruddha Chatterjee1,2, Peter A Stockwell3, Euan J Rodger1,2
1Department of Pathology, Dunedin School of Medicine, University of Otago, 270 Great King Street, Dunedin 9054, New Zealand.
Aim:
The Cancer Genome Atlas contains multiple levels of genomic data (mutation, gene expression, DNA methylation, copy number variation) for 33 cancer types for almost 11,000 patients. However, a dearth of appropriate software tools makes it difficult for bench scientists to use these data effectively.
Materials & Methods:
Here, we present a suite of flexible, fast and command line-based scripts that will allow retrieval and analysis of DNA methylation (tool: scan_tcga_methylation.awk), mRNA (tool: scan_tcga_mRNA.awk) and miRNA expression (tool: scan_tcga_miRNAs.awk) from cancer genome atlas network level 3 data.
Results:
We demonstrate the utility of these tools by analyzing DNA methylation and mRNA expression signatures of 60 frequently deregulated cancer genes and also of 30 miRNAs in primary (n = 102) and metastatic melanoma patients (n = 367).
Conclusion:
Our analysis illustrates the validity of the scan_tcga tools and reveals the epigenomic signatures and importance of identifying smaller patient subgroups with distinct molecular profiles.
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