ArticleGenome biology2025
DAGIP: alleviating cell-free DNA sequencing biases with optimal transport.
Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Epigenomic modifications define chromatin states to regulate cell-free DNA fragmentomics.Nature communications · 2026Article
- The Clinical Utility of Cell-Free DNA in Brain Tumor Management: A Comprehensive Review.Journal of molecular neuroscience : MN · 2025Review
- Cross-dataset pan-cancer detection by correlating cell-free DNA fragment coverage with open chromatin sites across cell types.Nature communications · 2025Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Cell-free DNA (cfDNA) is a rich source of biomarkers for various pathophysiological conditions. Preanalytical variables, such as the library preparation protocol or sequencing platform, are major confounders of cfDNA analysis. We present DAGIP, a novel data correction method that builds on optimal transport theory and deep learning, which explicitly corrects for the effect of such preanalytical variables and can infer technical biases. Our method improves cancer detection and copy number alteration analysis by alleviating the sources of variation that are not of biological origin. It also enhances fragmentomic analysis of cfDNA. DAGIP allows the integration of cohorts from different studies.
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Registered trials
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