DEG-by-Index Ratio Transformation Normalization with Blood RNA-Seq Enhances Early and Consistent Detection of Mouse...

Area of Science:

• Biomedical research
• Genomics
• Cancer biology

Background:

• Blood RNA-Seq data variability can mask tumor response signals.
• Conventional normalization methods (RLE/DESeq2, TMM/edgeR) often fail to detect these changes consistently.

Purpose of the Study:

• To evaluate the efficacy of DiRT (DEG-by-index Ratio Transformation) for analyzing blood RNA-Seq data in mouse tumorigenesis models.
• To compare DiRT's performance against standard normalization techniques.

Main Methods:

• Application of DiRT to 111 blood RNA-Seq datasets from mouse tumorigenesis models.
• Comparison of DiRT with RLE/DESeq2 and TMM/edgeR normalization methods.
• KEGG pathway analysis of differentially expressed genes (DEGs) identified by DiRT.

Main Results:

• DiRT achieved clearer separation between tumor and control samples starting from three days post-induction.
• DiRT maintained consistent marker signals throughout disease progression, unlike standard methods.
• DiRT identified enrichment in the platelet activation signaling pathway, a finding missed by conventional methods.

Conclusions:

• DiRT enhances sensitivity and reproducibility in blood RNA-Seq analysis for tumor development studies.
• DiRT enables earlier and more consistent detection of transcriptional changes compared to RLE/DESeq2 and TMM/edgeR.
• DiRT analysis highlights the platelet activation pathway in tumor progression.