Evidence map›Paper›PMID 41300367›Full record

ArticleBiology2025

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

Sang Woon Shin, Ji Ae Kim, Jong-Hoon Kim, Jun Hyoung Jeon, Kunhyang Park, Dae-Soo Kim, Jong Soon Kang, Myeong Youl Lee, Doo-Sang Park, SooJin Lee and 1 more

Abstract read
In one paragraph

Article in Biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Sang Woon ShinIndependent Researcher, 1045 Whirlaway Lane, Cherry Hill, NJ 08002, USA.ORCID 0000-0001-9467-0803
Ji Ae KimCore Research Facility & Analysis Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.
Jong-Hoon KimMicrobiome Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.
Jun Hyoung JeonCore Research Facility & Analysis Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.
Kunhyang ParkCore Research Facility & Analysis Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.
Dae-Soo KimDepartment of Digital Bio Technology Innovation, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.
Jong Soon KangLaboratory Animal Resource and Research Center, Korea Research Institute of Bioscience and Biotechnology, 30 Yeongudanjiro, Cheongju 28116, Republic of Korea.
Myeong Youl LeeLaboratory Animal Resource and Research Center, Korea Research Institute of Bioscience and Biotechnology, 30 Yeongudanjiro, Cheongju 28116, Republic of Korea.
Doo-Sang ParkBiological Resource Center, Korea Research Institute of Bioscience and Biotechnology, Jeongeup 56212, Republic of Korea.
SooJin LeeDepartment of Microbiology and Molecular Biology, Chungnam National University, Daejeon 34134, Republic of Korea.ORCID 0000-0002-0383-5025
Hyun-Woo OhCore Research Facility & Analysis Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.ORCID 0000-0003-3720-1896

Funding

Korea Research Institute of Bioscience and Biotechnology KGM1022511National Research Foundation of Korea 2022H1D3A2A01053247
6 · The paper itself

Abstract

Variability in blood RNA-Seq data can obscure transcriptional changes that reflect tumor responses, and conventional normalization methods such as RLE/DESeq2 or TMM/edgeR often fail to capture these changes consistently. To address this challenge, we applied DiRT (DEG-by-index Ratio Transformation), a normalization and analysis strategy previously used in insect models, to 111 blood RNA-Seq datasets from mouse tumorigenesis models. DiRT achieved clearer separation between tumor and control samples as early as three days after tumor induction and maintained consistent marker signals across all stages of disease progression. In contrast, standard methods typically revealed differences only at later or scattered time points. KEGG pathway analysis further showed that DiRT-derived differentially expressed genes (DEGs) were enriched in the platelet activation signaling pathway, a pathway not identified using RLE/DESeq2 or TMM/edgeR. These findings demonstrate that DiRT enhances both sensitivity and reproducibility, enabling earlier and more consistent detection of transcriptional changes in blood during tumor development.

Indexed as

DEG-by-index Ratio Transformationdifferentially expressed genesnormalizationRNA-Seqtumorigenesis

Identifiers

PMID41300367
PMCPMC12650743

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.